Breast Cancer Node Research Articles

DOP66 INSPIRE: Preliminary data from an observational post-marketing registry on the effectiveness and safety of darvadstrocel in patients with Crohn’s Disease and complex perianal fistulas

Abstract Background Darvadstrocel (DVS), a suspension of expanded allogeneic adipose-derived mesenchymal stem cells, is approved for the treatment of complex Crohn’s perianal fistulas (CPF). INSPIRE (EUPAS24267) is a European observational post-approval study evaluating real-world effectiveness and safety of DVS in patients with complex CPF for up to 36 months. Here we report preliminary clinical and safety outcomes from INSPIRE. Methods Patients with complex CPF who had received DVS according to local standard practice were eligible to enrol. Clinical response (closure of ≥50% of external openings [EOs]) and clinical remission (closure of all EOs) of DVS-treated fistulas that were draining at baseline, were evaluated in the all-treated (AT; received ≥1 dose of DVS with an evaluation for fistula response after 6 months) and per-protocol (PP; received DVS as per label-approved guidelines) cohorts. Treatment-emergent adverse events (TEAEs), serious TEAEs and AEs of special interest were reported for the safety cohort (all patients treated with DVS). Results As of April 2023, 652 patients had enrolled (Table 1). Complete data to evaluate 12-month clinical response and remission were available for 134 (AT cohort) and 124 (PP cohort) patients, of whom 79.9% (AT, n = 107) and 79.8% (PP, n = 99) had a clinical response and 76.1% (AT, n = 102) and 76.6% (PP, n = 95) had clinical remission (Figure 1). From baseline to Month 12, there was a decrease in the mean (standard deviation [SD]) Perianal Disease Activity Index score (–3.5 [3.3]; n/N = 96/302 and –3.7 [3.2]; n/N = 89/249) and a decrease in the mean (SD) Harvey–Bradshaw Index for Crohn’s disease activity (-0.3 [2.8]; n/N = 102/302 and -0.4 [2.9]; n/N = 95/249) in the AT and PP cohorts, respectively. Complete safety data were available for 619 patients (median [min–max] follow-up 480 [6–1595]) days. Overall, 26% (n = 162) had ≥1 TEAE and 10% (n = 63) ≥1 serious TEAE. The most frequent TEAEs were anal abscess (6.9%), COVID-19 (1.9%) and proctalgia (1.1%). No deaths were reported. One breast cancer lymph node metastasis and one ovarian epithelial cancer were reported; both events were confounded by immunosuppressant treatment and were not considered related to DVS treatment. Conclusion These preliminary data are consistent with the pivotal ADMIRE-CD study and demonstrate a single dose of DVS in patients with complex CPF is associated with positive clinical outcomes in up to 80% of patients, and a favourable safety profile, both of which are maintained after 12 months. The inherent limitations of registry-based studies mean these data should be interpreted with caution. However, the ongoing INSPIRE study will provide longer follow-up data to confirm these observations with respect to any study limitations.

Analysis of false reasons based on the artificial intelligence RRCART model to identify frozen sections of lymph nodes in breast cancer.

Breast cancer is the most common malignant tumor in the world. Intraoperative frozen section of sentinel lymph nodes is an important basis for determining whether axillary lymph node dissection is required for breast cancer surgery. We propose an RRCART model based on a deep-learning network to identify metastases in 2362 frozen sections and count the wrongly identified sections and the associated reasons. The purpose is to summarize the factors that affect the accuracy of the artificial intelligence model and propose corresponding solutions. We took the pathological diagnosis of senior pathologists as the gold standard and identified errors. The pathologists and artificial intelligence engineers jointly read the images and heatmaps to determine the locations of the identified errors on sections, and the pathologists found the reasons (false reasons) for the errors. Through NVivo 12 Plus, qualitative analysis of word frequency analysis and nodal analysis was performed on the error reasons, and the top-down error reason framework of "artificial intelligence RRCART model to identify frozen sections of breast cancer lymph nodes" was constructed based on the importance of false reasons. There were 101 incorrectly identified sections in 2362 slides, including 42 false negatives and 59 false positives. Through NVivo 12 Plus software, the error causes were node-coded, and finally, 2 parent nodes (high-frequency error, low-frequency error) and 5 child nodes (section quality, normal lymph node structure, secondary reaction of lymph nodes, micrometastasis, and special growth pattern of tumor) were obtained; among them, the error of highest frequency was that caused by normal lymph node structure, with a total of 45 cases (44.55%), followed by micrometastasis, which occurred in 30 cases (29.70%). The causes of identification errors in examination of sentinel lymph node frozen sections by artificial intelligence are, in descending order of influence, normal lymph node structure, micrometastases, section quality, special tumor growth patterns and secondary lymph node reactions. In this study, by constructing an artificial intelligence model to identify the error causes of frozen sections of lymph nodes in breast cancer and by analyzing the model in detail, we found that poor quality of slices was the preproblem of many identification errors, which can lead to other errors, such as unclear recognition of lymph node structure by computer. Therefore, we believe that the process of artificial intelligence pathological diagnosis should be optimized, and the quality control of the pathological sections included in the artificial intelligence reading should be carried out first to exclude the influence of poor section quality on the computer model. For cases of micrometastasis, we suggest that by differentiating slices into high- and low-confidence groups, low-confidence micrometastatic slices can be separated for manual identification. The normal lymph node structure can be improved by adding samples and training the model in a targeted manner.

Evaluation of blood supply and metabolism in tumor, axillary lymph node and normal breast tissue with F-18 FDG PET/CT in breast cancer: comparison with pathological prognostic factors

Background and purposePerfusion parameters obtained in F-18 FDG PET/CT performed for staging purposes in breast cancers may provide additional information about tumor biology as well as glucose metabolism. The aim of this study was to evaluate throughout F-18 FDG PET/CT the relationship between blood flow and glucose metabolism and histological parameters of the primary tumor, normal mammary gland, and axillary lymph nodes in breast cancer patients.Materials and methodsSixty six female patients (mean age 51 y ± 12,81) were prospectively included to this study. We performed dynamic blood flow (f) study that started with 296–444 MBq (8–12 mCi) F-18 FDG injection and lasted for 10 minutes, and glucose metabolism (m) imaging one hour later. On each frame, mean activity concentration (AC) values (Bq/mL) were recorded on a spherical volume of interest (VOI) having a volume of ~ 1 cm3 on the hottest voxel of primary tumor (T), across normal breast gland (NG) and ipsilaterally axillary lymph nodes (iLN). Correlations among PET parameters and estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (c-erbB2) and Ki67 index were analyzed.ResultsT volume (TV) ranged from 1.1 to 85.28 cm3 [median (IR): 6.44 (11.78)]. There were positive correlations between c-erbB2 and TACf and between c-erbB2 and iLNACf (p = 0.045, r = + 0.248; p = 0.050, r = + 0.242). In the ER positive (ERP) patients, TV and TACm were significantly lower than those of ER negative (ERN) (respectively p = 0.044 and p = 0.041). In patients with two positive Ki-67 indices, iLN-SUVmax was significantly higher than one-positive patients (p = 0.020). There was a negative correlation between NGACm and histological grade of tumor (p = 0.005, r = − 0.365).ConclusionsBreast cancer shows differences in progression, metastasis and survival due to its diversity in terms of molecular, biological and angiogenesis. High glucose metabolism in breast cancers is associated with tumor aggressiveness. Being able to examine tumor tissue characteristics such as blood flow and glucose metabolism with a single diagnostic technique and to reveal its relationship with histological parameters can provide a reliable pretherapeutic evaluation in breast cancers.

Retrospective validation study of an artificial neural network-based preoperative decision-support tool for noninvasive lymph node staging (NILS) in women with primary breast cancer (ISRCTN14341750)

BackgroundSurgical sentinel lymph node biopsy (SLNB) is routinely used to reliably stage axillary lymph nodes in early breast cancer (BC). However, SLNB may be associated with postoperative arm morbidities. For most patients with BC undergoing SLNB, the findings are benign, and the procedure is currently questioned. A decision-support tool for the prediction of benign sentinel lymph nodes based on preoperatively available data has been developed using artificial neural network modelling.MethodsThis was a retrospective geographical and temporal validation study of the noninvasive lymph node staging (NILS) model, based on preoperatively available data from 586 women consecutively diagnosed with primary BC at two sites. Ten preoperative clinicopathological characteristics from each patient were entered into the web-based calculator, and the probability of benign lymph nodes was predicted. The performance of the NILS model was assessed in terms of discrimination with the area under the receiver operating characteristic curve (AUC) and calibration, that is, comparison of the observed and predicted event rates of benign axillary nodal status (N0) using calibration slope and intercept. The primary endpoint was axillary nodal status (discrimination, benign [N0] vs. metastatic axillary nodal status [N+]) determined by the NILS model compared to nodal status by definitive pathology.ResultsThe mean age of the women in the cohort was 65 years, and most of them (93%) had luminal cancers. Approximately three-fourths of the patients had no metastases in SLNB (N0 74% and 73%, respectively). The AUC for the predicted probabilities for the whole cohort was 0.6741 (95% confidence interval: 0.6255–0.7227). More than one in four patients (n = 151, 26%) were identified as candidates for SLNB omission when applying the predefined cut-off for lymph node-negative status from the development cohort. The NILS model showed the best calibration in patients with a predicted high probability of healthy axilla.ConclusionThe performance of the NILS model was satisfactory. In approximately every fourth patient, SLNB could potentially be omitted. Considering the shift from postoperatively to preoperatively available predictors in this validation study, we have demonstrated the robustness of the NILS model. The clinical usability of the web interface will be evaluated before its clinical implementation.Trial registrationRegistered in the ISRCTN registry with study ID ISRCTN14341750.Date of registration 23/11/2018.

Domestic system for fluorescent diagnostics in breast cancer: pros and cons

To analyze the effectiveness of identifying the sentinel lymph node in breast cancer using the «MARS» system for fluorescent diagnostics in near infrared light. There were 51 patients with breast cancer cT0-2N0M0 between July 2023 and October 2023. Mean age of patients was 52.3 years. Invasive ductal carcinoma was diagnosed in 39 (76.5%) patients, invasive lobular carcinoma - in 8 (15.7%) patients, other forms of breast cancer - in 4 (7.8%) patients. Sentinel lymph node was successfully identified in all cases (n=51). A total of 122 sentinel lymph nodes were detected and mapped (2.4 nodes per a patient). The MARS system for intraoperative fluorescence diagnostics in near-infrared light is effective for identifying the sentinel lymph node in breast cancer.

B Cells and IL-21-Producing Follicular Helper T Cells Cooperate to Determine the Dynamic Alterations of Premetastatic Tumor Draining Lymph Nodes of Breast Cancer.

Metastasis is the major cause of cancer-related death, and lymph node is the most common site of metastasis in breast cancer. However, the alterations that happen in tumor-draining lymph nodes (TDLNs) to form a premetastatic microenvironment are largely unknown. Here, we first report the dynamic changes in size and immune status of TDLNs before metastasis in breast cancer. With the progression of tumor, the TDLN is first enlarged and immune-activated at early stage that contains specific antitumor immunity against metastasis. The TDLN is then contracted and immunosuppressed at late stage before finally getting metastasized. Mechanistically, B and follicular helper T (Tfh) cells parallelly expand and contract to determine the size of TDLN. The activation status and specific antitumor immunity of CD8+ T cells in the TDLN are determined by interleukin-21 (IL-21) produced by Tfh cells, thus showing parallel changes. The turn from activated enlargement to suppressed contraction is due to the spontaneous contraction of germinal centers mediated by follicular regulatory T cells. On the basis of the B-Tfh-IL-21-CD8+ T cell axis, we prove that targeting the axis could activate TDLNs to resist metastasis. Together, our findings identify the dynamic alterations and regulatory mechanisms of premetastatic TDLNs of breast cancer and provide new strategies to inhibit lymph node metastasis.

Retrospective audit of the yield of internal mammary lymph node dissection and literature review in the management of breast cancer.

Treatment of lymph node basins is prognostic and therapeutic for axillary lymph nodes (ALN) as well as internal mammary lymph nodes (IMLNs) in breast cancer. IMLNs can be the first echelon node for the inner/central quadrants of the breast. We evaluated the yield of IMLN dissection (IMLND) mainly in patients with inner and central tumors. IMLND was performed in 199 patients between 2000 and 2018, 127 of whom had tumors in the inner/ central quadrants. Clinico-pathological data were retrieved from Electronic Medical Records (EMR). The median age was 50 (range: 24-81). Primary surgery was performed in 82 (41.2%), while 117 (58.8%) were operated post-chemotherapy. Overall, 124/199 (62.3%) had nodes identified in the specimen, more often in primary (61/82, 74.4%) than post-chemotherapy settings (63/117, 53.8%) (P = 0.003). A median of 1 (average: 1.24, range: 0-7) lymph nodes was dissected, and 1 (average: 1.5, range: 1-4) was involved. IMLN was positive in 46/199 (23.1%) patients, not significantly different in primary (21/82, 25.6%) versus post-chemotherapy (25/117, 21.4%) settings (P = 0.545). IMLN was involved in 44.8% of patients with ≥4 involved ALN and 8.2% with uninvolved ALN (P < 0.001). In the absence of ALN involvement and <2cm pT size, 9% of patients had positive IMLN in inner/central quadrant tumors. In univariate analysis, ALN positivity (P < 0.001), pT size (P = 0.023), and grade (P = 0.041) in primary and ALN involvement (P = 0.011) in post-chemotherapy patients were associated with IMLN involvement. On logistic regression, tumor size (OR: 13.914, P = 0.017) and ALN involvement (OR: 11.400, P = 0.005) in primary surgery and ALN involvement (OR: 7.294, P = 0.003) in post-chemotherapy patients correlated with IMLN involvement. In inner/central quadrant tumors, IMLN is more likely involved with high ALN burden and tumor size >2 cm, whereas those with ≤2cm inner/central quadrant tumors and negative ALN have <10% probability of IMLN involvement.

Deep Learning based Intelligent Tumor Analytics Framework for Quantitative Grading and Analyzing Cancer Metastasis: Case of Lymph Node Breast Cancer

Deep Learning based Intelligent Tumor Analytics Framework for Quantitative Grading and Analyzing Cancer Metastasis: Case of Lymph Node Breast Cancer

Cross-attention-based saliency inference for predicting cancer metastasis on whole slide images.

Although multiple instance learning (MIL) methods are widely used for automatic tumor detection on whole slide images (WSI), they suffer from the extreme class imbalance WSIs containing small tumors where the tumor may include only a few isolated cells. For early detection, it is important that MIL algorithms can identify small tumors. Existing studies have attempted to address this issue using attention-based architectures and instance selection-based methodologies but have not produced significant improvements. This paper proposes crossattention-based salient instance inference MIL (CASiiMIL), which involves a novel saliency-informed attention mechanism to identify small tumors (e.g., breast cancer lymph node micro-metastasis) on WSIs without needing any annotations. In addition to this new attention mechanism, we introduce a negative representation learning algorithm to facilitate the learning of saliencyinformed attention weights for improved sensitivity on tumor WSIs. The proposed model outperforms the state-ofthe-art MIL methods on two popular tumor metastasis detection datasets. The proposed approach demonstrates great cross-center generalizability, high accuracy in classifying WSIs with small tumor lesions, and excellent interpretability attributed to the saliency-informed attention weights. We expect that the proposed method will pave the way for training algorithms for early tumor detection on large datasets where acquiring fine-grained annotations is is not practical.

Sonographic Characteristics of Enlarged Axillary Lymph Node in Breast Cancer

Background: Breast cancer, the most prevalent cancer in women globally, presents unique challenges in Pakistan, particularly due to the younger average age of diagnosis compared to Western countries. Accurate assessment of axillary lymph nodes using ultrasound (US) is essential for effective breast cancer staging and prognosis. Objective: This study aimed to evaluate the sonographic characteristics of axillary lymph nodes in breast cancer patients in Pakistan and to assess the diagnostic efficacy of ultrasound in differentiating between benign and malignant lymph nodes. Methods: Conducted at Shalamar Hospital, Lahore, this cross-sectional study spanned four months and included 150 breast cancer patients aged 45-70 years, selected through convenient sampling. Ultrasound examinations were performed using a GE Ultrasound Machine Evolsion E7 with a linear probe (7.5-12Hz). Key sonographic parameters, including the shape, size (length and width), and echogenicity of lymph nodes, were meticulously recorded and analyzed by using SPSS 24.0. Results: The average length and width of lymph nodes were 5.86 mm (SD = 1.35) and 3.90 mm (SD = 0.77), respectively. A significant proportion of lymph nodes (74.2%) presented with a round shape in patients experiencing pain, and a predominance of hyperechoic nodes was noted, diverging from established literature that often associates hypoechoic nodes with malignancy. Additionally, an irregular shape was identified as a potential predictive marker for axillary lymph node metastasis. Conclusion: This study highlights the efficacy of axillary sonography in diagnosing axillary metastasis in breast cancer, showing moderate sensitivity and substantial specificity. It also identifies a notable association between older age and the likelihood of axillary lymph node metastasis, especially in women in their forties.

A multivariable model of ultrasound and clinicopathological features for predicting axillary nodal burden of breast cancer: potential to prevent unnecessary axillary lymph node dissection

BackgroundTo develop a clinical model for predicting high axillary nodal burden in patients with early breast cancer by integrating ultrasound (US) and clinicopathological features.Methods and materialsPatients with breast cancer who underwent preoperative US examination and breast surgery at the Affiliated Hospital of Nantong University (centre 1, n = 250) and at the Affiliated Hospital of Jiangsu University (centre 2, n = 97) between January 2012 and December 2016 and between January 2020 and March 2022, respectively, were deemed eligible for this study (n = 347). According to the number of lymph node (LN) metastasis based on pathology, patients were divided into two groups: limited nodal burden (0–2 metastatic LNs) and heavy nodal burden (≥ 3 metastatic LNs). In addition, US features combined with clinicopathological variables were compared between these two groups. Univariate and multivariate logistic regression analysis were conducted to identify the most valuable variables for predicting ≥ 3 LNs in breast cancer. A nomogram was then developed based on these independent factors.ResultsUnivariate logistic regression analysis revealed that the cortical thickness (p < 0.001), longitudinal to transverse ratio (p = 0.001), absence of hilum (p < 0.001), T stage (p = 0.002) and Ki-67 (p = 0.039) were significantly associated with heavy nodal burden. In the multivariate logistic regression analysis, cortical thickness (p = 0.001), absence of hilum (p = 0.042) and T stage (p = 0.012) were considered independent predictors of high-burden node. The area under curve (AUC) of the nomogram was 0.749.ConclusionOur model based on US variables and clinicopathological characteristics demonstrates that can help select patients with ≥ 3 LNs, which can in turn be helpful to predict high axillary nodal burden in early breast cancer patients and prevent unnecessary axillary lymph node dissection.

A machine-learning approach based on multiparametric MRI to identify the risk of non-sentinel lymph node metastasis in patients with early-stage breast cancer.

It has been reported that patients with early breast cancer with 1-2 positive sentinel lymph nodes have a lower risk of non-sentinel lymph node (NSLN) metastasis and cannot benefit from axillary lymph node dissection. To develop the potential of machine learning based on multiparametric magnetic resonance imaging (MRI) and clinical factors for predicting the risk of NSLN metastasis in breast cancer. This retrospective study included 144 patients with 1-2 positive sentinel lymph node breast cancer. Multiparametric MRI morphologic findings and the detailed demographical characteristics of the primary tumor and axillary lymph node were extracted. The logistic regression, support vector classification, extreme gradient boosting, and random forest algorithm models were established to predict the risk of NSLN metastasis. The prediction efficiency of a machine-learning-based model was evaluated. Finally, the relative importance of each input variable was analyzed for the best model. Of the 144 patients, 80 (55.6%) developed NSLN metastasis. A total of 24 imaging features and 14 clinicopathological features were analyzed. The extreme gradient boosting algorithm had the strongest prediction efficiency with an area under curve of 0.881 and 0.781 in the training set and test set, respectively. Five main factors for the metastasis of NSLN were found, including histological grade, cortical thickness, fatty hilum, short axis of lymph node, and age. The machine-learning model incorporating multiparametric MRI features and clinical factors can predict NSLN metastasis with high accuracy for breast cancer and provide predictive information for clinical protocol.

Relationship of the integrin profile of the primary tumor to metastasis to regional lymph nodes in breast cancer

Background. Breast cancer ranks first in the structure of cancer morbidity and mortality. Involvement of a large number of regional lymph nodes is considered a poor prognostic outcome. The mechanisms of development of lymphogenous metastasis in general and common in particular are not fully understood. Integrins are involved in the metastatic process by mediating tumor cell invasion and adhesion to vascular endothelium.&#x0D; Aim. To study the role of integrins in lymphogenous metastasis.&#x0D; Materials and methods. The study included 72 patients diagnosed with invasive breast carcinoma of no special type who underwent surgical treatment on the basis of the cancer research institute national research medical center. The average age reached 51.2 years. In accordance with the indications and morphological data, the patients underwent antitumor treatment. The tissue of the primary tumor obtained by trepanbiopsy. Histological and immunohistochemical examination was carried out according to the standard method. In primary tumor cells, the presence or absence of cytoplasmic or membrane/cytoplasmic colocalization of CD61 (Integrin beta 3), CD104 (Integrin beta 4), CD51 (Integrin alpha-V) expression was assessed. When statistically processing the results, Fisher's test and one-way regression analysis were used.&#x0D; Results. In the N3 group, the frequency of cytoplasmic expression of CD 61 was higher at the trend level (40.9 and 18%; p=0.074). In the group of patients with N3, positive cytoplasmic expression of CD104 (37.5 and 15.0%; p=0.029) and membrane and cytoplasmic colocalization (52.6 and 15.1%; p=0.004) were more often detected. In the group with N1 and N2, membrane and cytoplasmic colocalization of CD104 expression was less common (15.8 and 54.7%; p=0.006). When studying the expression frequency of CD51 integrin, no significant differences were found depending on the severity of lymphogenous metastasis.&#x0D; Conclusion. Expression of CD104 in primary tumor cells is strongly associated with widespread lymphogenous metastasis. Studies of the role of integrins in the development of lymphogenous metastasis are promising for predicting the prevalence of this process in the preoperative period and for searching for methods of influencing the tumor.

Factors Predictive of Positive Lymph Nodes for Breast Cancer.

Axillary node status is an important prognostic factor in breast cancer. The primary aim was to evaluate tumor size and other characteristics relative to axillary disease. Single institution retrospective chart review of stage I-III breast cancer patients collected demographic and clinical/pathologic data from 1998-2019. Student's t-test, Chi-squared test (or Fisher exact test if applicable), and logistic regression models were used for testing the association of pN+ to predictive variables. Of 728 patients (mean age 59 yrs) with mean follow up of 50 months, 86% were estrogen receptor +, 10% Her2+, 78% ER+HER2-negative, and 10% triple-negative. In total, 351/728 (48.2%) were pN+ and mean tumor size was larger in pN+ cases compared to pN- cases (mean = 27.7 mm versus 15.5 mm) (p < 0.001). By univariate analysis, pN+ was associated with lymphovascular invasion (LVI), higher grade, Her2, and histology (p < 0.005). Tumor-to-nipple distance was shorter in pN+ compared to pN- (45 mm v. 62 mm; p< 0.001). Age < 60, LVI, recurrence, mastectomy, larger tumor size, and shorter tumor-nipple distance were associated with 3+ positive nodes (p < 0.05). Larger tumor size and shorter tumor-nipple distance were associated with higher lymph node positivity. Age less than 60, LVI, recurrence, mastectomy, larger tumor size, and shorter tumor-nipple distance were all associated with 3+ positive lymph nodes.

Immune checkpoint status and exhaustion-related phenotypes of CD8+ T cells from the tumor-draining regional lymph nodes in breast cancer.

Functional status of T cells determines the responsiveness of cancer patients to immunotherapeutic interventions. Even though T cell-mediated immunity is inaugurated in the tumor-adjacent lymph nodes, peripheral blood has been routinely sampled for testing the immunological assays. The purpose of this study is to determine the immune checkpoint molecule expression and the exhaustion-related phenotype of cytotoxic T cells in the regional lymph nodes from breast cancer patients. Multicolor immunophenotyping was used to determine the expression of PD-1, TIM-3, LAG3, CTLA-4, CCR7, CD45RO, CD127, CD25, CXCR5, and ICOS molecules on CD3+ CD4- CD56- CD8+ cytotoxic T cells freshly obtained from the lymph nodes and the peripheral blood samples of the breast cancer patients. The results were assessed together with the clinical data. A population of cytotoxic T cells was noted with high PD-1 and CXCR5 expression in the lymph nodes of the breast cancer patients. Co-expression of PD-1, CXCR5, TIM-3, and ICOS indicated a follicular helper T cell (Tfh)-like, exhaustion-related immunophenotype in these cytotoxic T cells. Only a minor population with CTLA-4 and LAG3 expression was noted. The PD-1+ CXCR5+ cytotoxic T cells largely displayed CD45RO+ CCR7+ central memory markers. The amount of CXCR5-expressing PD-1- cytotoxic T cells was elevated in the lymph nodes of the patients. The regional lymph nodes of breast cancer patients harbor Tfh-like exhausted cytotoxic T lymphocytes with high PD-1 and TIM-3 checkpoint molecule expression. The immunological conditions in the regional lymph nodes should be implicated for immune checkpoint immunotherapy (ICI) of cancer.

Optimization of supraclavicular lymph node clinical target volume delineation in high-risk breast cancer: a single center experience and recommendation

BackgroundProphylactic irradiation of supraclavicular lymph node drainage areas can improve the regional control rate of lymph node-positive or lymph node-negative disease but a locally-advanced stage breast cancer, and it can reduce breast cancer-related mortality. However, many controversies exist in the clinical target volume delineation of supraclavicular lymph node drainage in patients with breast cancer.MethodsWe retrospectively analyzed 42 patients with breast cancer and supraclavicular lymph node metastasis at our hospital between January 2017 and December 2021. Among these cases, 32 were locally advanced and 10 were stage IV at initial treatment. A patient with breast cancer who did not undergo dissection of the supraclavicular and infraclavicular lymph nodes at our hospital was selected as a standard patient. A contrast-enhanced computed tomography (CT) scan for positioning was used as a template image, and blood vessels, muscles, and bony landmarks were used as references for positioning. The metastatic supraclavicular lymph nodes were identified in all enrolled patients and projected into the template CT images.ResultsThe metastastic pattern of supraclavicular lymph node in breast cancer was proposed: distribution along the posterolateral border of the internal jugular vein (medial supraclavicular group) and along the transverse jugular vein (lateral supraclavicular group). We theorized that the lateral and posterior borders of the clinical target volume in the supraclavicular region should include the lymph nodes in the posterior triangle of the neck (level V) in high-risk individuals. If the metastatic axillary lymph node is extensive, then the superior border of the supraclavicular region should be moved upward appropriately.ConclusionsThis study analyzed patients with breast cancer and supraclavicular lymph node metastasis at initial treatment, explored the metastastic pattern of supraclavicular lymph node, and applied anatomical knowledge to further optimize the target volume delineation of supraclavicular lymph node drainage area in high-risk breast cancer.

SIX1 amplification modulates stemness and tumorigenesis in breast cancer

BackgroundSine oculis homeobox homolog 1 (SIX1) is a transcription factor that has recently been identified as a crucial regulator of embryonic development and tumorigenesis. SIX1 is upregulated in different types of tumors, including breast cancer. However, the role and mechanism of SIX1 upregulation in breast cancer carcinogenesis remains uncertain.MethodsIn this study, we utilized various databases such as UALCAN, TCGA, STRING, and Kaplan–Meier Plotter to investigate the mRNA expression, prognosis, transcriptional profile changes, signal pathway rewiring, and interaction with cancer stem cells of SIX1 in breast cancer. We also conducted both in vitro and in vivo experiments to validate its positive regulation effect on breast cancer stem cells.ResultsOur findings demonstrated that the expression of SIX1 varies among different subtypes of breast cancer and that it upregulates breast cancer grading and lymph node metastasis. Besides, SIX1 participates in the rewiring of several cancer signaling pathways, including estrogen, WNT, MAPK, and other pathways, and interacts with cancer stem cells. SIX1 showed a significant positive correlation with breast cancer stem cell markers such as ALDH1A1, EPCAM, ITGB1, and SOX2. Moreover, our in vitro and in vivo experiments confirmed that SIX1 can promote the increase in the proportion of stem cells and tumor progression.ConclusionsAltogether, our results suggest that SIX1 plays an essential regulatory role in breast cancer's occurrence, and its amplification can be utilized as a diagnostic and prognostic predictor. The interaction between SIX1 and cancer stem cells may play a critical role in regulating breast cancer's initiation and metastasis.

Nonmetastatic Axillary Lymph Nodes Have Distinct Morphology and Immunophenotype in Obese Patients with Breast Cancer at Risk for Metastasis

Obese breast cancer patients have worse outcomes than their normal weight counterparts, with a 50% to 80% increased rate of axillary nodal metastasis. Recent studies suggest a link between increased lymph node adipose tissue and breast cancer nodal metastasis. Further investigation into potential mechanisms underlying this link may reveal potential prognostic utility of fat-enlarged lymph nodes in breast cancer patients. This study uses a deep learning model to identify morphological differences in non-metastatic axillary nodes between obese, node-positive and node-negative breast cancer patients. The model was developed using nested cross-validation on 180 cases and achieved an AUC of 0.67 in differentiating patients using hematoxylin and eosin stained whole-slide images. The top predictive patches from the slides according to the model were reviewed by a pathologist and their morphological differences were quantified. This analysis showed an increased average adipocyte size (p-value=0.004), increased white space between lymphocytes (p-value<0.0001), and increased red blood cells (p-value<0.001) in non-metastatic lymph nodes of node-positive patients. Preliminary immunohistochemistry analysis on a subset of 30 patients showed a trend of decreased CD3 expression and increased leptin expression in fat-replaced axillary lymph nodes of obese, node-positive patients. These findings suggest a novel direction to further investigate the interaction between lymph node adiposity, lymphatic dysfunction, and breast cancer nodal metastases, highlighting a possible prognostic tool for obese breast cancer patients.

Optical Imaging in Human Lymph Node Specimens for Detecting Breast Cancer Metastases: A Review.

Assessment of regional lymph node status in breast cancer is of important staging and prognostic value. Even though formal histological examination is the currently accepted standard of care, optical imaging techniques have shown promising results in disease diagnosis. In the present article, we review six spectroscopic techniques and focus on their use as alternative tools for breast cancer lymph node assessment. Elastic scattering spectroscopy (ESS) seems to offer a simple, cost-effective, and reproducible method for intraoperative diagnosis of breast cancer lymph node metastasis. Optical coherence tomography (OCT) provides high-resolution tissue scanning, along with a short data acquisition time. However, it is relatively costly and experimentally complex. Raman spectroscopy proves to be a highly accurate method for the identification of malignant axillary lymph nodes, and it has been further validated in the setting of head and neck cancers. Still, it remains time-consuming. Near-infrared fluorescence imaging (NIRF) and diffuse reflectance spectroscopy (DFS) are related to significant advantages, such as deep tissue penetration and efficiency. Fourier-transform infrared spectroscopy (FTIR) is a promising method but has significant drawbacks. Nonetheless, only anecdotal reports exist on their clinical use for cancerous lymph node detection. Our results indicate that optical imaging methods can create informative and rapid tools to effectively guide surgical decision-making.

Advantages of contrast-enhanced ultrasound in the localization and diagnostics of sentinel lymph nodes in breast cancer.

Sentinel lymph nodes (SLNs) are the first station of lymph nodes that extend from the breast tumor to the axillary lymphatic drainage. The pathological status of these LNs can predict that of the entire axillary lymph node. Therefore, the accurate identification of SLNs is necessary for sentinel lymph node biopsy (SLNB) to replace axillary lymph node dissection (ALND). The quality of life and prognosis of breast cancer patients are related to proper surgical treatment after the precise identification of SLNs. Some of the SLN tracers that have been identified include radioisotope, nano-carbon, indocyanine green (ICG), and methylene blue (MB). However, these tracers have certain limitations, such as pigmentation, radiation dangers, and the requirement for costly detection equipment. Ultrasound contrast agents (UCAs) have good specificity and sensitivity, and thus can compensate for some shortcomings of the mentioned tracers. This technique is also being applied to SLNB in patients with breast cancer, and can even provide an initial judgment on SLN status. Contrast-enhanced ultrasound (CEUS) has the advantages of high distinguishability, simple operation, no radiation harm, low cost, and accurate localization; therefore, it is expected to replace the traditional biopsy methods. In addition, it can significantly enhance the accuracy of SLN localization and shorten the operation time.