Expression and prognostic value of HER-2/neu in primary breast cancer with sentinel lymph node metastasis

Tumor enhancement and shrinkage pattern in dynamic contrast-enhanced magnetic resonance imaging for predicting pathologic complete response after human epidermal growth factor receptor 2 (HER2)-targeted therapy in breast cancer

Background

Targeted therapy with neoadjuvant chemotherapy for patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer has increased the rates of pathological complete response (pCR) and breast preservation surgery and improved the overall disease-free survival rate. This study aimed to determine whether tumor enhancement and shrinkage patterns in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can predict the efficacy of targeted therapy in patients with HER2-positive breast cancer and differentiate pCR from non-pCR.

Methods

The data of 64 patients with HER2-positive breast cancer who received targeted therapy prior to surgery were retrospectively collected. All patients had complete postoperative pathological data. The pretreatment evaluation of the tumor enhancement pattern and the shrinkage pattern after two treatment cycles were assessed. The difference in the enhancement and shrinkage patterns between the pCR and non-pCR groups was evaluated via the χ2 test. Logistic regression analysis was used to assess the value of enhancement and shrinkage patterns for predicting pCR in patients with HER2-positive breast cancer.

Results

There were statistically significant differences in tumor size, estrogen receptor (ER) status, lymph node metastasis, enhancement pattern, and shrinkage pattern between the pCR and non-pCR cases. Patients with a tumor size ≤20 mm were likely to achieve pCR. ER status, lymph node metastasis, and enhancement and shrinkage patterns each had good precision for predicting pCR, and the combination of enhancement and shrinkage patterns had the highest prediction accuracy. Multivariate logistic regression analysis indicated that only enhancement pattern had a significant predictive value.

Conclusions

Among patients with HER2-positive breast cancer, those with tumor size ≤20 mm, ER-negative status, no lymph node metastases, and mass enhancement and concentric shrinkage patterns are more likely to achieve pCR. Mass enhancement combined with concentric shrinkage had the highest accuracy in predicting pCR, indicating that preoperative imaging may be useful for guiding clinical decisions regarding targeted treatments.

Factors Predictive of Positive Lymph Nodes for Breast Cancer

BACKGROUND

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.

MATERIALS AND METHODS

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.

RESULTS

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).

CONCLUSIONS

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.

Factors Influencing Lymph Node Positivity in HER2/neu+ Breast Cancer Patients

Axillary lymph node metastases are a key prognostic factor in breast cancer treatment. Our aim was to evaluate how tumor size, tumor location, and imaging results correlate to axillary lymph node diseases for patients with stage I-III HER2/neu+ breast cancer. This is a single-institution retrospective chart review of female breast cancer patients diagnosed with primary invasive Her2/neu+ breast cancer who were treated with upfront surgical resection from 2000–2021. Of 75 cases, 44/75 (58.7%) had nodal metastasis, and there was a significant association of larger tumor size to nodal metastases (p ≤ 0.001). Patients with negative nodes had a smaller mean tumor size (n = 30; 15.10 mm) than patients with positive nodes (n = 45; 23.9 mm) (p = 0.002). Preoperative imaging detected suspicious nodes in 36 patients, and ultrasound detected the most positive nodes (14/18; p = 0.027). Our data confirms that tumor size at diagnosis is correlated with a higher likelihood of axillary involvement in patients with Her2/neu+ breast cancer; notably, a large proportion of Her2/neu+ breast cancers have metastatic involvement of axillary lymph nodes even with small primary lesions.

Survival and clinicopathological significance of blood vessel invasion in operable breast cancer: a systematic review and meta-analysis

BACKGROUND

Lymphovascular invasion, including lymphatic-vessel invasion and blood-vessel invasion, plays an important role in distant metastases. The metastatic pattern of blood-vessel invasion may differ from that of lymphatic-vessel invasion. However, its prognostic significance in breast cancer remains controversial. We evaluated the role of blood-vessel invasion in the prognosis of operable breast-cancer patients and its association with clinicopathological characteristics.

METHODS

We systematically searched EMBASE, PubMed, the Cochrane Library and Web of Science for studies in English through December 2020. Disease-free survival, overall survival and cancer-specific survival were the primary outcomes. Pooled hazard ratios and 95% confidence intervals were assessed using a random-effects model.

RESULTS

Twenty-seven studies involving 7954 patients were included. Blood-vessel invasion occurred in 20.4% of tumor samples. Pooled results showed significant associations of blood-vessel invasion with worse disease-free survival (hazard ratio = 1.82; 95% confidence interval = 1.43-2.31) and overall survival (hazard ratio = 1.86; 95% confidence interval = 1.16-2.99) in multivariate analyses. The results of the univariate analyses were similar. Among the clinicopathological factors, blood-vessel invasion was associated with larger tumor size, lymph-node metastasis, nonspecific invasive type, higher histological grade, estrogen receptor-negative breast cancer, human epidermal growth factor receptor 2-positive breast cancer and lymphatic-vessel invasion. In the lymph-node-negative subgroup analyses, the presence of blood-vessel invasion led to poorer disease-free survival (hazard ratio = 2.46; 95%confidence interval = 1.64-3.70) and overall survival (hazard ratio = 2.94; 95%confidence interval = 1.80-4.80).

CONCLUSIONS

We concluded that blood-vessel invasion is an independent predictor of poor prognosis in operable breast cancer and is associated with aggressive clinicopathological features. Breast-cancer patients with blood-vessel invasion require more aggressive treatments after surgery.

Prognostic and predictive biomarkers for response to neoadjuvant chemoradiation in esophageal adenocarcinoma

Background

Esophageal adenocarcinoma is a lethal disease. For locally advanced patients, neoadjuvant chemoradiotherapy followed by surgery is the standard of care. Risk stratification relies heavily on clinicopathologic features, particularly pathologic response, which is inadequate, therefore establishing the need for new and reliable biomarkers for risk stratification.

Methods

Thirty four patients with locally advanced esophageal adenocarcinoma were analyzed, of which 21 received a CROSS regimen with carboplatin, paclitaxel, and radiation. Capture-based targeted sequencing was performed on the paired baseline and post-treatment samples. Differentially mutated gene analysis between responders and non-responders of treatment was performed to determine predictors of response. A univariate Cox proportional hazard regression was used to examine associations between gene mutation status and overall survival.

Results

A 3-gene signature, based on mutations in EPHA5, BCL6, and ERBB2, was identified that robustly predicts response to the CROSS regimen. For this model, sensitivity was 84.6% and specificity was 100%. Independently, a 9 gene signature was created using APC, MAP3K6, ETS1, CSF3R, PDGFRB, GATA2, ARID1A, PML, and FGF6, which significantly stratifies patients into risk categories, prognosticating for improved relapse-free (p = 4.73E-03) and overall survival (p = 3.325E-06). The sensitivity for this model was 73.33% and the specificity was 94.74%.

Conclusion

We have identified a 3-gene signature (EPHA5, BCL6, and ERBB2) that is predictive of response to neoadjuvant chemoradiotherapy and a separate prognostic 9-gene classifier that predicts survival outcomes. These panels provide significant potential for personalized management of locally advanced esophageal cancer.

Prediction of lymph node metastasis in patients with breast invasive micropapillary carcinoma based on machine learning and SHapley Additive exPlanations framework

Abstract

Background and purpose: Machine learning (ML) is applied for outcome prediction and treatment support. This study aims to develop different ML models to predict risk of axillary lymph node metastasis (LNM) in breast invasive micropapillary carcinoma (IMPC) and to explore the risk factors of LNM.

Methods

From the Surveillance, Epidemiology, and End Results (SEER) database and the records of our hospital, a total of 1547 patients diagnosed with breast IMPC were incorporated in this study. The ML model is built and the external validation is carried out. SHapley Additive exPlanations (SHAP) framework was applied to explain the optimal model; multivariable analysis was performed with logistic regression (LR); and nomograms were constructed according to the results of LR analysis.

Results

Age and tumor size were correlated with LNM in both cohorts. The luminal subtype is the most common in patients, with the tumor size <=20mm. Compared to other models, Xgboost was the best ML model with the biggest AUC of 0.813 (95% CI: 0.7994 - 0.8262) and the smallest Brier score of 0.186 (95% CI: 0.799-0.826). SHAP plots demonstrated that tumor size was the most vital risk factor for LNM. In both training and test sets, Xgboost had better AUC (0.761 vs 0.745; 0.813 vs 0.775; respectively), and it also achieved a smaller Brier score (0.202 vs 0.204; 0.186 vs 0.191; 0.220 vs 0.221; respectively) than the nomogram model based on LR in those three different sets. After adjusting for five most influential variables (tumor size, age, ER, HER-2, and PR), prediction score based on the Xgboost model was still correlated with LNM (adjusted OR:2.73, 95% CI: 1.30-5.71, P=0.008).

Conclusions

The Xgboost model outperforms the traditional LR-based nomogram model in predicting the LNM of IMPC patients. Combined with SHAP, it can more intuitively reflect the influence of different variables on the LNM. The tumor size was the most important risk factor of LNM for breast IMPC patients. The prediction score obtained by the Xgboost model could be a good indicator for LNM.

Metabolomics research on potential role for 9-cis-retinoic acid in breast cancer progression

Deciphering the molecular networks that discriminate organ-confined breast cancer from metastatic breast cancer may lead to the identification of critical biomarkers for breast cancer invasion and aggressiveness. Here metabolomics, a global study of metabolites, has been applied to explore the metabolic alterations that characterize breast cancer progression. We profiled a total of 693 metabolites across 87 serum samples related to breast cancer (46 clinically localized and 41 metastatic breast cancer) and 49 normal samples. These unbiased metabolomic profiles were able to distinguish normal individuals, clinically localized and metastatic breast cancer patients. 9-cis-Retinoic acid, an isomer of all-trans retinoic acid, was identified as a differential metabolite that significantly decreased during breast cancer progression to metastasis, and its levels were also reduced in urine samples from biopsy-positive breast cancer patients relative to biopsy-negative individuals and in invasive breast cancer cells relative to benign MCF-10A cells. The addition of exogenous 9-cis-retinoic acid to MDA-MB-231 cells and knockdown of aldehyde dehydrogenase 1 family member A1, a regulatory enzyme for 9-cis-retinoic acid, remarkably impaired cell invasion and migration, presumably through preventing the key regulator cofilin from activation and inhibiting MMP2 and MMP9 expression. Taken together, our study showed the potential inhibitory role for 9-cis-retinoic acid in breast cancer progression by attenuating cell invasion and migration.

Significance and prognostic role of human epidermal growth factor receptor 2 and RAB1A expression in gastric cancer

Human epidermal growth factor receptor 2 (HER-2) has an important clinical role in various cancers. However, the prognostic impact of HER-2 in gastric cancer (GC) is controversial. RAB1A is an important small molecule in the mechanistic target of rapamycin signalling pathway, which is one of the downstream signalling pathways of the epidermal growth factor receptor family. In recent years, the aberrant expression of RAB1A has been reported in a number of tumours, but its regulation in GC has not been extensively examined. Therefore, the present study investigated the expression pattern and prognostic significance of HER-2 and RAB1A in gastric adenocarcinoma (CAG). A comprehensive analysis was performed to examine the expression level of HER-2 and RAB1A in 280 cases of paired paraffin-embedded GAC tissues and an additional 120 archived GAC tissue samples. HER-2 and RAB1A protein expression was assessed by immunohistochemistry and cases with a 2+ score for HER-2 expression levels were subjected to fluorescence in situ hybridization to determine the HER-2 amplification status. Furthermore, HER-2 and RAB1A mRNA expression was quantified by reverse transcription-quantitative polymerase chain reaction. The comparison of continuous data between two groups was performed using a paired-samples t-test. Clinical correlations were determined using Pearson's Chi-square and Fisher's exact tests. Kaplan-Meier survival curves were used to estimate overall survival (OS). Cox proportional hazards models were used to determine associations between HER-2 and RAB1A expression and outcomes. Regression analyses were performed to detect the correlation between the mRNA levels of HER-2 and RAB1A in GAC tissues. It was observed that RAB1A was significantly overexpressed in GAC tissues compared with normal tissues (P<0.001). Approximately 12.86% of the 280 GAC patients had HER-2 amplification. Additionally, RAB1A expression was significantly associated with a short OS (P<0.001) but there were no significant differences in survival between the HER-2 high-expression group and the HER-2 low-expression group. Additionally, the co-expression of HER-2 and RAB1A indicated poorer OS than the overexpression of each protein (P=0.001), and the two factors were significantly positively correlated in GAC (P=0.012). These findings may be used to further explore the molecular mechanisms and regulatory associations among signalling pathways in GC.

The development of CAR design for tumor CAR-T cell therapy

In recent years, the chimeric antigen receptor modified T cells (Chimeric antigen receptor T cells, CAR-T) immunotherapy has developed rapidly, which has been considered the most promising therapy. Efforts to enhance the efficacy of CAR-based anti-tumor therapy have been made, such as the improvement of structures of CAR-T cells, including the development of extracellular antigen recognition receptors, intracellular co-stimulatory molecules and the combination application of CARs and synthetic small molecules. In addition, effects on the function of the CAR-T cells that the space distance between the antigen binding domains and tumor targets and the length of the spacer domains have are also being investigated. Given the fast-moving nature of this field, it is necessary to make a summary of the development of CAR-T cells. In this review, we mainly focus on the present design strategies of CAR-T cells with the hope that they can provide insights to increase the anti-tumor efficacy and safety.