Breast Cancer-Major changes in the American Joint Committee on Cancer eighth edition cancer staging manual

Prelude to malignancy: A gene expression signature in normal mammary gland from breast cancer patients suggests pre-tumorous alterations and is associated with adverse outcomes

Despite advances in early detection and treatment strategies, breast cancer recurrence and mortality remain a significant health issue. Recent insights suggest the prognostic potential of microscopically healthy mammary gland, in the vicinity of the breast lesion. Nonetheless, a comprehensive understanding of the gene expression profiles in these tissues and their relationship to patient outcomes remain missing. Furthermore, the increasing trend towards breast-conserving surgery may inadvertently lead to the retention of existing cancer-predisposing mutations within the normal mammary gland. This study assessed the transcriptomic profiles of 242 samples from 83 breast cancer patients with unfavorable outcomes, including paired uninvolved mammary gland samples collected at varying distances from primary lesions. As a reference, control samples from 53 mammoplasty individuals without cancer history were studied. A custom panel of 634 genes linked to breast cancer progression and metastasis was employed for expression profiling, followed by whole-transcriptome verification experiments and statistical analyses to discern molecular signatures and their clinical relevance. A distinct gene expression signature was identified in uninvolved mammary gland samples, featuring key cellular components encoding keratins, CDH1, CDH3, EPCAM cell adhesion proteins, matrix metallopeptidases, oncogenes, tumor suppressors, along with crucial genes (FOXA1, RAB25, NRG1, SPDEF, TRIM29, and GABRP) having dual roles in cancer. Enrichment analyses revealed disruptions in epithelial integrity, cell adhesion, and estrogen signaling. This signature, named KAOS for Keratin-Adhesion-Oncogenes-Suppressors, was significantly associated with reduced tumor size but increased mortality rates. Integrating molecular assessment of non-malignant mammary tissue into disease management could enhance survival prediction and facilitate personalized patient care.

Deep learning Radiomics Based on Two-Dimensional Ultrasound for Predicting the Efficacy of Neoadjuvant Chemotherapy in Breast Cancer

We investigate the predictive value of a comprehensive model based on preoperative ultrasound radiomics, deep learning, and clinical features for pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) for the breast cancer. We enrolled 155 patients with pathologically confirmed breast cancer who underwent NAC. The patients were randomly divided into the training set and the validation set in the ratio of 7:3. The deep learning and radiomics features of pre-treatment ultrasound images were extracted, and the random forest recursive elimination algorithm and the least absolute shrinkage and selection operator were used for feature screening and DL-Score and Rad-Score construction. According to multifactorial logistic regression, independent clinical predictors, DL-Score, and Rad-Score were selected to construct the comprehensive prediction model DLRC. The performance of the model was evaluated in terms of its predictive effect, and clinical practicability. Compared to the clinical, radiomics (Rad-Score), and deep learning (DL-Score) models, the DLRC accurately predicted the pCR status, with an area under the curve (AUC) of 0.937 (95%CI: 0.895-0.970) in the training set and 0.914 (95%CI: 0.838-0.973) in the validation set. Moreover, decision curve analysis confirmed that the DLRC had the highest clinical value among all models. The comprehensive model DLRC based on ultrasound radiomics, deep learning, and clinical features can effectively and accurately predict the pCR status of breast cancer after NAC, which is conducive to assisting clinical personalized diagnosis and treatment plan.

The contrast-free diffusion MRI multiple index for the early prediction of pathological response to neoadjuvant chemotherapy in breast cancer

Early tumor response prediction can help avoid overtreatment with unnecessary chemotherapy sessions. It is important to determine whether multiple apparent diffusion coefficient indices (S index, ADC-diff) are effective in the early prediction of pathological response to neoadjuvant chemotherapy (NAC) in breast cancer (BC). Patients with stage II and III BCs who underwent T1WI, diffusion-weighted imaging (DWI), and dynamic contrast-enhanced MRI using a 3 T system were included. They were divided into two groups: major histological responders (MHRs, Miller-Payne G4/5) and nonmajor histological responders (nMHRs, Miller-Payne G1-3). Three b values were used for DWI to derive the S index; ADC-diff values were obtained using b = 0 and 1000 s/mm2. The different interquartile ranges of percentile S-index and ADC-diff values after treatment were calculated and compared. The assessment was performed at baseline and after two and four NAC cycles. A total of 59 patients were evaluated. There are some correlations of interquartile ranges of S-index parameters and ADC-diff values with histopathological prognostic factors (such as estrogen receptor and human epidermal growth factor receptor 2 expression, all p < 0.05), but no significant differences were found in some other interquartile ranges of S-index parameters or ADC-diff values between progesterone receptor positive and negative or for Ki-67 tumors (all P > 0.05). No differences were found in the dynamic contrast-enhanced MRI characteristics between the two groups. HER-2 expression and kurtosis of the S-index distribution were screened out as independent risk factors for predicting MHR group (p < 0.05, area under the curve (AUC) = 0.811) before NAC. After early NAC (two cycles), only the 10th percentile S index was statistically significant between the two groups (p < 0.05, AUC = 0.714). No significant differences were found in ADC-diff value at any time point of NAC between the two groups (P > 0.1). These findings demonstrate that the S-index value may be used as an early predictor of pathological response to NAC in BC; the value of ADC-diff as an imaging biomarker of NAC needs to be further confirmed by ongoing multicenter prospective trials.

Prognostic values of tumor size and location in early stage endometrial cancer patients who received radiotherapy

OBJECTIVE

To investigate the correlation between tumor size, tumor location, and prognosis in patients with early-stage endometrial cancer (EC) receiving adjuvant radiotherapy.

METHODS

Data of patients who had been treated for stage I-II EC from March 1999 to September 2017 in 13 tertiary hospitals in China was screened. Cox regression analysis was performed to investigate associations between tumor size, tumor location, and other clinical or pathological factors with cancer-specific survival (CSS) and distant metastasis failure-free survival (DMFS). The relationship between tumor size as a continuous variable and prognosis was demonstrated by restricted cubic splines. Prognostic models were constructed as nomograms and evaluated by Harrell's C-index, calibration curves and receiver operating characteristic (ROC) curves.

RESULTS

The study cohort comprised 805 patients with a median follow-up of 61 months and a median tumor size of 3.0 cm (range 0.2-15.0 cm). Lower uterine segment involvement (LUSI) was found in 243 patients (30.2%). Tumor size and LUSI were identified to be independent prognostic factors for CSS. Further, tumor size was an independent predictor of DMFS. A broadly positive relationship between poor survival and tumor size as a continuous variable was visualized in terms of hazard ratios. Nomograms constructed and evaluated for CSS and DMFS had satisfactory calibration curves and C-indexes of 0.847 and 0.716, respectively. The area under the ROC curves for 3- and 5-year ROC ranged from 0.718 to 0.890.

CONCLUSION

Tumor size and LUSI are independent prognostic factors in early-stage EC patients who have received radiotherapy. Integrating these variables into prognostic models would improve predictive ability.

Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor A (VEGF-A) expressions in Ethiopian female breast cancer and their association with histopathologic features

BACKGROUND

Epidermal growth factor receptor (EGFR) and vascular endothelial growth factor receptor (VEGF) play important role in breast tumor growth, invasion, metastasis, patient survival and drug resistance. The aim of this study was to evaluate the protein expression status of EGFR and VEGF-A, as well as their association with hormone receptor status and histopathological characteristics in the invasive type of female breast cancer among Ethiopians.

METHOD

The primary breast tumor tissues were obtained from 85 Ethiopian invasive breast cancer cases that underwent modified radical mastectomy (MRM) from June 2014 to June 2015. Their FFPE blocks were analyzed for EGFR and VEGF protein expressions using immunohistochemical techniques. The expressions were also correlated with histopathologic features.

RESULT

Epidermal growth factor receptor over-expression was observed in 22% of the tumor samples. VEGF-A expression was negative in 13.41%, low in 63.41%, moderate in 20.73%, and high in 2.44%. EGFR expression, but not VEGF-A, showed a significant inverse correlation with both estrogen receptor (ER) (P = 0.01) and progesterone receptor (PR) statuses (P = 0.04). EGFR and VEGF expressions did not show significant association with tumor size, grade, lymph node status or age at diagnosis.

CONCLUSION

Epidermal growth factor receptor expression was most likely associated with ER and PR negative tumors. Assessments of multiple molecular markers aid to understand the biological behavior of the disease in Ethiopian population. It might also help to predict which group of patients might get more benefit from the selected treatment strategies and which are not.

Diagnostic performance of TILs-US score and LPBC in biopsy specimens for predicting pathological complete response in patients with breast cancer

BACKGROUND

Tumor-infiltrating lymphocytes-ultrasonography (TILs-US) score is used to predict lymphocyte-predominant breast cancer (LPBC) in surgical specimens. We aimed to compare diagnostic performance of TILs-US score for predicting pathological complete response (pCR) with that of LPBC in biopsy specimens.

METHODS

TILs ≥ 50% in biopsy specimens was defined as biopsy-LPBC, and TILs-US score ≥ 4 was categorized as TILs-US score-high. Basic nomogram for pCR was developed using stepwise logistic regression based on the smallest Akaike Information Criterion, and biopsy-LPBC and TILs-US score nomograms were developed by integrating biopsy-LPBC or TILs-US scores into a basic nomogram. The diagnostic performance of the nomograms for pCR was compared using area under the curve (AUC), categorical net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS

This retrospective study evaluated 118 patients with breast cancer, including 33 (28.0%) with biopsy-LPBC, 52 (44.1%) with TILs-US score-high, with 34 (28.8%) achieving pCR. The sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and AUC for predicting pCR were 0.53, 0.82, 2.96, 0.57, and 0.68, respectively, for biopsy-LPBC, and 0.76, 0.69, 2.47, 0.34, and 0.73, respectively, for TILs-US score. The biopsy-LPBC nomogram showed significant improvements in categorical NRI (p = 0.023) and IDI (p = 0.007) but not in AUC (p = 0.25), compared with the basic nomogram. The TILs-US nomogram exhibited significant improvements in AUC (p = 0.039), categorical NRI (p = 0.010), and IDI (p < 0.001).

CONCLUSIONS

The TILs-US score may serve as a novel marker for prediction of pCR in patients with breast cancer. An external validation study is warranted to confirm our findings.

Subdivision of M1 category and prognostic stage for de novo metastatic breast cancer to enhance prognostic prediction and guide the selection of locoregional therapy

BACKGROUND

Although de novo metastatic breast cancer (dnMBC) is acknowledged as a heterogeneous disease, the current staging systems do not distinguish between patients within the M1 or stage IV category. This study aimed to refine the M1 category and prognostic staging for dnMBC to enhance prognosis prediction and guide the choice of locoregional treatment.

METHODS

We selected patients with dnMBC from the SEER database (2010-2019), grouping them into training (N = 8048) and internal validation (N = 3450) cohorts randomly at a 7:3 ratio. An independent external validation cohort (N = 660) was enrolled from dnMBC patients (2010-2023) treated in three hospitals. Nomogram-based risk stratification was employed to refine the M1 category and prognostic stage, incorporating T/N stage, histologic grade, subtypes, and the location and number of metastatic sites. Both internal and external validation sets were used for validation analyses.

RESULTS

Brain, liver, or lung involvement and multiple metastases were independent prognostic factors for overall survival (OS). The nomogram-based stratification effectively divided M1 stage into three groups: M1a (bone-only involvement), M1b (liver or lung involvement only, with or without bone metastases), and M1c (brain metastasis or involvement of both liver and lung, regardless of other metastatic sites). Only subtype and M1 stage were included to define the final prognostic stage. Significant differences in OS were observed across M1 and prognostic subgroups. Patients with the M1c stage benefited less from primary tumor surgery in comparison with M1a stage.

CONCLUSION

Subdivision of the M1 and prognostic stage could serve as a supplement to the current staging guidelines for dnMBC and guide locoregional treatment.

Vitamin D receptor is associated with prognostic characteristics of breast cancer after neoadjuvant chemotherapy-an observational study

Background

Breast cancer (BC) is the most commonly diagnosed malignant tumor in women. The disease and its subsequent treatment pose a serious burden on the quality of life of patients. Neoadjuvant chemotherapy (NAC) has become one of the crucial strategies for the management of BC. Since the identification of the vitamin D receptor (VDR) in mammary tissues, extensive mechanistic research has been conducted on its function. The expression of VDR in BC cells and the tumor microenvironment could be a new prognostic factor for BC after NAC.

Patients and Methods

This observational, single-center study compared data from clinical and histopathological records of 111 female subjects with the expression of VDR in different cellular and tissue components of breast specimens obtained from surgery after NAC. VDR expression was evaluated using an immunoreactive score assigned after immunohistochemistry. Intergroup comparisons and logistic regression were used to identify associations between VDR expression and clinicopathological features of BC.

Results

We found that the expression of VDR is associated with various clinical features (i.e., age, menopausal status, and NAC cycle number) and characteristics of prognostic significance, such as residual cancer burden class. Logistic regression analysis revealed that the expression of VDR in the nuclei and cytoplasm of surrounding normal mammary cells predicted vascular invasion and lymph node involvement.

Conclusions

The expression of VDR in tumor cells and their microenvironment is related to the clinicopathological characteristics of BC after NAC.

Breast conserving surgery with intraoperative electron beam radiation therapy for low-risk breast cancer: Five-year follow-up of 306 patients

Recent studies have reported a higher than expected risk of ipsilateral breast tumor recurrence (IBTR) after breast conserving surgery (BCS) and a single dose of electron beam intra-operative radiotherapy (IORT). This finding was the rationale to perform a retrospective single center cohort study evaluating the oncologic results of consecutive patients treated with BCS and IORT. Women were eligible if they had clinical low-risk (N0, ≤2 cm unifocal, Bloom and Richardson grade 1-2), estrogen receptor-positive and human-epidermal-growth-factor-receptor-2-negative breast cancer. Prior to BCS, pN0 status was determined by sentinel lymph node biopsy. Data on oncologic follow-up were analyzed. Between 2012 and 2019, 306 consecutive patients were treated and analyzed, with a median age of 67 (50-86) years at diagnosis. Median follow-up was 60 (8-120) months. Five-year cumulative risk of IBTR was 13.4% (95% confidence interval [CI] 9.4-17.4). True in field recurrence was present in 3.9% of the patients. In 4.6% of the patients, the IBRT was classified as a local recurrence due to seeding of tumor cells in the cutis or subcutis most likely related to percutaneous biopsy. In 2.9% of the patients, the IBRT was a new outfield primary tumor. Three patients had a regional lymph node recurrence and two had distant metastases as first event. One breast cancer-related death was observed. Estimated 5-year overall survival was 89.8% (95% CI 86.0-93.6). In conclusion, although some of IBTR cases could have been prevented by adaptations in biopsy techniques and patient selection, BCS followed by IORT was associated with a substantial risk of IBTR.

Newer combination treatments for breast cancer coexisting with acute myeloid leukemia in the novel regimens era: A case report and literature review

The occurrence of acute myeloid leukemia (AML) with a simultaneous diagnosis of breast cancer (BC) is rarely reported in the literature. The present study reports the case of a 50-year-old female patient diagnosed with AML coexisting with metastatic BC. Following one cycle of treatment with azacytidine in combination with oral venetoclax for AML, the patient achieved complete remission with incomplete hematological recovery. In addition, the mass in the left breast was smaller following adjuvant chemotherapy. However, due to a refusal from the patient to accept an allogeneic hematopoietic stem cell transplantation (allo-HSCT), the patient succumbed 3 months after diagnosis due to septic shock from neutropenia following the third cycle of chemotherapy. Altogether, the present case report highlighted the application of venetoclax, an oral selective B-cell lymphoma-2 inhibitor, both in hematologic malignancies and solid neoplasms, as an effective therapeutic regimen. Considering the fatality rate associated with AML, allo-HSCT is the only available strategy that can be used to achieve the long-term survival of patients with AML and BC.

The effect of total size, area, and volume of lesions in multifocal/multicentric breast cancers and unifocal breast cancers on survival: An observational study

In this study, we aimed to investigate the prognostic effect of the classifications made according to the stage of the largest lesion diameter (T-max stage) and of the sum of the longest diameters of the lesions (T-sum stage), the largest area stage (A-max stage), the sum of the largest areas (A-sum stage), the highest volume stage (V-max stage), the sum of the highest volume (V-sum stage) on disease-free survival, and overall survival (OS) in multifocal/multicentric breast cancers (MMBCs) and unifocal breast cancers (UBCs). The study included a total of 769 patients either with MMBC (n = 128) or UBC (n = 641) who underwent surgery between 2006 and 2015. In the analysis, the median age of 769 patients was 53.0 (20.0-94.0) years, and 16.6% of these 769 patients were MMBC and 83.4% were UBC. In multivariate analysis, lymphovascular invasion (LVİ), estrogen receptor, and nodal status were common independent prognostic factors, whereas T-max stage [(HR: 1.17) (CI 95%: 1.03-1.33) (P = .018)] was a prognostic factor for OS. In multivariate analysis, the T-max stage is an independent risk factor for OS. Therefore, T-max should be continued to be used for measurement and T-stage should be used for classification in MMBCs/UBCs.

The efficacy of screening with FDG-PET/CT for distant metastases in breast cancer patients scheduled for neoadjuvant systemic therapy

PURPOSE

This study aims to identify which breast cancer patients benefit from the routine use of FDG-PET/CT in a large cohort of patients scheduled for neoadjuvant systemic therapy (NST).

METHODS

A total of 1337 breast cancer patients eligible for NST were identified from a retrospective database between 2011 and 2020 at a single tertiary care hospital. All patients underwent staging with FDG-PET/CT prior to NST. The incidence and extent of asymptomatic distant metastases in different patient subgroups were determined, as well as the impact on treatment. Logistic regression analysis was used to identify prognostic patient and tumor characteristics.

RESULTS

FDG-PET/CT detected distant metastases in 109 patients (8%). Initial clinical stage was a prognostic factor for the presence of distant metastases, with a significantly higher risk for stage 2b and 3 as opposed to lower stages (p < 0.001). The incidence of distant metastases was 3% (4/125) for stage 1, 2% (8/534) for stage 2a, 7% (24/354) for stage 2b and 23% (73/324) for stage 3. Other characteristics such as age, tumor subtype, histological type and grade were not correlated with the risk of distant metastases. Among the subset of patients with distant metastases, 46% received palliative treatment, while the remaining 54% were diagnosed with oligometastatic breast cancer and were treated with curative intent.

CONCLUSION

The results of the current study support the routine use of FDG-PET/CT for the detection of distant metastases in breast cancer patients with initial clinical stage 2b and 3, regardless of tumor subtype.

Prediction of Microinvasion in Breast Ductal Carcinoma in Situ Using Conventional Ultrasound Combined with Contrast-Enhanced Ultrasound Features: A Two-Center Study

BACKGROUND

To develop and validate a model based on conventional ultrasound (CUS) and contrast-enhanced ultrasound (CEUS) features to preoperatively predict microinvasion in breast ductal carcinoma in situ (DCIS).

PATIENTS AND METHODS

Data from 163 patients with DCIS who underwent CUS and CEUS from the internal hospital was retrospectively collected and randomly apportioned into training and internal validation sets in a ratio of 7:3. External validation set included 56 patients with DCIS from the external hospital. Univariate and multivariate logistic regression analysis were performed to determine the independent risk factors associated with microinvasion. These factors were used to develop predictive models. The performance was evaluated through calibration, discrimination, and clinical utility.

RESULTS

Multivariate analysis indicated that centripetal enhancement direction (odds ratio [OR], 13.268; 95% confidence interval [CI], 3.687-47.746) and enhancement range enlarged on CEUS (OR, 4.876; 95% CI, 1.470-16.181), lesion size of ≥20 mm (OR, 3.265; 95% CI, 1.230-8.669) and calcification detected on CUS (OR, 5.174; 95% CI, 1.903-14.066) were independent risk factors associated with microinvasion. The nomogram incorporated the CUS and CEUS features achieved favorable discrimination (AUCs of 0.850, 0.848, and 0.879 for the training, internal and external validation datasets), with good calibration. The nomogram outperformed the CUS model and CEUS model (all P < .05). Decision curve analysis confirmed that the predictive nomogram was clinically useful.

CONCLUSION

The nomogram based on CUS and CEUS features showed promising predictive value for the preoperative identification of microinvasion in patients with DCIS.

Role of [18F]FDG PET/CT in patients with invasive breast carcinoma of no special type: Literature review and comparison between guidelines

PURPOSE

The recently released EANM/SNMMI guideline, endorsed by several important clinical and imaging societies in the field of breast cancer (BC) care (ACR, ESSO, ESTRO, EUSOBI/ESR, EUSOMA), emphasized the role of [18F]FDG PET/CT in management of patients with no special type (NST) BC. This review identifies and summarizes similarities, discrepancies and novelties of the EANM/SNMMI guideline compared to NCCN, ESMO and ABC recommendations.

METHODS

The EANM/SNMMI guideline was based on a systematic literature search and the AGREE tool. The level of evidence was determined according to NICE criteria, and 85 % agreement or higher was reached regarding each statement. Comparisons with NCCN, ESMO and ABC guidelines were examined for specific clinical scenarios in patients with early stage through advanced and metastatic BC.

RESULTS

Regarding initial staging of patients with NST BC, [18F]FDG PET/CT is the preferred modality in the EANM-SNMMI guideline, showing superiority as a single modality to a combination of contrast-enhanced CT of thorax-abdomen-pelvis plus bone scan in head-to-head comparisons and a randomized study. Its use is recommended in patients with clinical stage IIB or higher and may be useful in certain stage IIA cases of NST BC. In NCCN, ESMO, and ABC guidelines, [18F]FDG PET/CT is instead recommended as complementary to conventional imaging to solve inconclusive findings, although ESMO and ABC also suggest [18F]FDG PET/CT can replace conventional imaging for staging patients with high-risk and metastatic NST BC. During follow up, NCCN and ESMO only recommend diagnostic imaging if there is suspicion of recurrence. Similarly, EANM-SNMMI states that [18F]FDG PET/CT is useful to detect the site and extent of recurrence only when there is clinical or laboratory suspicion of recurrence, or when conventional imaging methods are equivocal. The EANM-SNMMI guideline is the first to emphasize a role of [18F]FDG PET/CT for assessing early metabolic response to primary systemic therapy, particularly for HER2+ BC and TNBC. In the metastatic setting, EANM-SNMMI state that [18F]FDG PET/CT may help evaluate bone metastases and determine early response to treatment, in agreement with guidelines from ESMO.

CONCLUSIONS

The recently released EANM/SNMMI guideline reinforces the role of [18F]FDG PET/CT in the management of patients with NST BC supported by extensive evidence of its utility in several clinical scenarios.

Exploring the behavioral intentions of PICC-related thrombosis prevention in breast cancer patients undergoing chemotherapy: a qualitative study based on theory of planned behavior

PURPOSE

To explore the behavioral intention of breast cancer patients undergoing chemotherapy to prevent PICC-related thrombosis based on the theory of planned behavior (TPB).

METHODS

This qualitative study employed purposive sampling and conducted semi-structured interviews with 14 breast cancer patients undergoing chemotherapy in the outpatient chemotherapy ward of a tertiary A-level comprehensive hospital in Beijing from July to August 2023. Data were analyzed using Colaizzi's descriptive analysis framework.

RESULTS

Data analysis identified 10 themes that were derived from 4 aspects. Regarding behavioral attitude, three themes were condensed: (1) Considering the benefits of preventive measures, (2) Simple and easy preventive measures, and (3) Underestimating the importance of PICC-related thrombosis prophylaxis. Subjective norms yielded two main themes and five sub-themes: (1) Support from those close to the patient motivates adherence to prophylaxis (support from the patient's family, healthcare professionals, and other patients) and (2) Patients are influenced by personal factors to form an internal driving force (physical symptoms, fear of PICC-related thrombosis). Regarding perceived behavioral control, three main themes and four sub-themes were extracted: (1) Obstacles before actual prevention exercise (prevention information, hard-to-remember information), (2) Forgetfulness is the main obstacle factor, and (3) Wanting to overcome barriers to adhere to regular prevention (confidence to overcome obstacles, hope to get support).

CONCLUSIONS

The impediments and facilitators identified in this study may provide a scientific foundation for subsequent targeted non-pharmacological preventive interventions for PICC-related thrombosis based on TPB in breast cancer patients undergoing chemotherapy. Special interventions should be designed for the patients in three areas: the patients themselves, the supporters around the patient, and the healthcare professionals.

Cross-modal deep learning model for predicting pathologic complete response to neoadjuvant chemotherapy in breast cancer

Pathological complete response (pCR) serves as a critical measure of the success of neoadjuvant chemotherapy (NAC) in breast cancer, directly influencing subsequent therapeutic decisions. With the continuous advancement of artificial intelligence, methods for early and accurate prediction of pCR are being extensively explored. In this study, we propose a cross-modal multi-pathway automated prediction model that integrates temporal and spatial information. This model fuses digital pathology images from biopsy specimens and multi-temporal ultrasound (US) images to predict pCR status early in NAC. The model demonstrates exceptional predictive efficacy. Our findings lay the foundation for developing personalized treatment paradigms based on individual responses. This approach has the potential to become a critical auxiliary tool for the early prediction of NAC response in breast cancer patients.

Multi-modality radiomics model predicts axillary lymph node metastasis of breast cancer using MRI and mammography

OBJECTIVES

We aimed to develop a multi-modality model to predict axillary lymph node (ALN) metastasis by combining clinical predictors with radiomic features from magnetic resonance imaging (MRI) and mammography (MMG) in breast cancer. This model might potentially eliminate unnecessary axillary surgery in cases without ALN metastasis, thereby minimizing surgery-related complications.

METHODS

We retrospectively enrolled 485 breast cancer patients from two hospitals and extracted radiomics features from tumor and lymph node regions on MRI and MMG images. After feature selection, three random forest models were built using the retained features, respectively. Significant clinical factors were integrated with these radiomics models to construct a multi-modality model. The multi-modality model was compared to radiologists' diagnoses on axillary ultrasound and MRI. It was also used to assist radiologists in making a secondary diagnosis on MRI.

RESULTS

The multi-modality model showed superior performance with AUCs of 0.964 in the training cohort, 0.916 in the internal validation cohort, and 0.892 in the external validation cohort. It surpassed single-modality models and radiologists' ALN diagnosis on MRI and axillary ultrasound in all validation cohorts. Additionally, the multi-modality model improved radiologists' MRI-based ALN diagnostic ability, increasing the average accuracy from 70.70 to 78.16% for radiologist A and from 75.42 to 81.38% for radiologist B.

CONCLUSION

The multi-modality model can predict ALN metastasis of breast cancer accurately. Moreover, the artificial intelligence (AI) model also assisted the radiologists to improve their diagnostic ability on MRI.

CLINICAL RELEVANCE STATEMENT

The multi-modality model based on both MRI and mammography images allows preoperative prediction of axillary lymph node metastasis in breast cancer patients. With the assistance of the model, the diagnostic efficacy of radiologists can be further improved.

KEY POINTS

• We developed a novel multi-modality model that combines MRI and mammography radiomics with clinical factors to accurately predict axillary lymph node (ALN) metastasis, which has not been previously reported. • Our multi-modality model outperformed both the radiologists' ALN diagnosis based on MRI and axillary ultrasound, as well as single-modality radiomics models based on MRI or mammography. • The multi-modality model can serve as a potential decision support tool to improve the radiologists' ALN diagnosis on MRI.

Characteristics of Invasive Cribriform Carcinoma

Invasive cribriform carcinoma (ICC) is a type of malignant tumor with slow growth and good prognosis. The study was a single center retrospective study. The percentage of ICC among patients diagnosed with breast cancer was 0.3% (8/2454 patients). All patients tested positive for estrogen or progesterone receptors and 12.5% (1/8) patients tested positive for human epidermal growth factor receptor type2 (HER2). The present study suggests that the clinicopathological features of ICC are low-grade hormone receptor-positive luminal type with a good prognosis. However, some patients were HER2-positive and require careful follow-up.

Assessing Axillary Lymph Node Burden and Prognosis in cT1-T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual-Institutional MRI Study

BACKGROUND

Pathological axillary lymph node (pALN) burden is an important factor for treatment decision-making in clinical T1-T2 (cT1-T2) stage breast cancer. Preoperative assessment of the pALN burden and prognosis aids in the individualized selection of therapeutic approaches.

PURPOSE

To develop and validate a machine learning (ML) model based on clinicopathological and MRI characteristics for assessing pALN burden and survival in patients with cT1-T2 stage breast cancer.

STUDY TYPE

Retrospective.

POPULATION

A total of 506 females (range: 24-83 years) with cT1-T2 stage breast cancer from two institutions, forming the training (N = 340), internal validation (N = 85), and external validation cohorts (N = 81), respectively.

FIELD STRENGTH/SEQUENCE

This study used 1.5-T, axial fat-suppressed T2-weighted turbo spin-echo sequence and axial three-dimensional dynamic contrast-enhanced fat-suppressed T1-weighted gradient echo sequence.

ASSESSMENT

Four ML methods (eXtreme Gradient Boosting [XGBoost], Support Vector Machine, k-Nearest Neighbor, Classification and Regression Tree) were employed to develop models based on clinicopathological and MRI characteristics. The performance of these models was evaluated by their discriminative ability. The best-performing model was further analyzed to establish interpretability and used to calculate the pALN score. The relationships between the pALN score and disease-free survival (DFS) were examined.

STATISTICAL TESTS

Chi-squared test, Fisher's exact test, univariable logistic regression, area under the curve (AUC), Delong test, net reclassification improvement, integrated discrimination improvement, Hosmer-Lemeshow test, log-rank, Cox regression analyses, and intraclass correlation coefficient were performed. A P-value <0.05 was considered statistically significant.

RESULTS

The XGB II model, developed based on the XGBoost algorithm, outperformed the other models with AUCs of 0.805, 0.803, and 0.818 in the three cohorts. The Shapley additive explanation plot indicated that the top variable in the XGB II model was the Node Reporting and Data System score. In multivariable Cox regression analysis, the pALN score was significantly associated with DFS (hazard ratio: 4.013, 95% confidence interval: 1.059-15.207).

DATA CONCLUSION

The XGB II model may allow to evaluate pALN burden and could provide prognostic information in cT1-T2 stage breast cancer patients.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY: Stage 2.

MRI features of breast cancer immunophenotypes with a focus on luminal estrogen receptor low positive invasive carcinomas

To compare the magnetic resonance imaging (MRI) features of different immunophenotypes of breast carcinoma of no special type (NST), with special attention to estrogen receptor (ER)-low-positive breast cancer. This retrospective, single-centre, Institutional Review Board (IRB)-approved study included 398 patients with invasive breast carcinoma. Breast carcinomas were classified as ER-low-positive when there was ER staining in 1-10% of tumour cells. Pretreatment MRI was reviewed to assess the tumour imaging features according to the 5th edition of the Breast Imaging Reporting and Data System (BI-RADS) lexicon. Of the 398 cases, 50 (12.6%) were luminal A, 191 (48.0%) were luminal B, 26 (6.5%) were luminal ER-low positive, 64 (16.1%) were HER2-overexpressing, and 67 (16.8%) were triple negative. Correlation analysis between MRI features and tumour immunophenotype showed statistically significant differences in mass shape, margins, internal enhancement and the delayed phase of the kinetic curve. An oval or round shape and rim enhancement were most frequently observed in triple-negative and luminal ER-low-positive tumours. Spiculated margins were most common in luminal A and luminal B tumours. A persistent kinetic curve was more frequent in luminal A tumours, while a washout curve was more common in the triple-negative, HER2-overexpressing and luminal ER-low-positive immunophenotypes. Multinomial regression analysis showed that luminal ER-low-positive tumours had similar results to triple-negative tumours for almost all variables. Luminal ER-low-positive tumours present with similar MRI findings to triple-negative tumours, which suggests that MRI can play a fundamental role in adequate radiopathological correlation and therapeutic planning in these patients.

Insights into the performance of PREDICT tool in a large Mainland Chinese breast cancer cohort: a comparative analysis of versions 3.0 and 2.2

BACKGROUND

PREDICT is a web-based tool for forecasting breast cancer outcomes. PREDICT version 3.0 was recently released. This study aimed to validate this tool for a large population in mainland China and compare v3.0 with v2.2.

METHODS

Women who underwent surgery for nonmetastatic primary invasive breast cancer between 2010 and 2020 from the First Affiliated Hospital of Wenzhou Medical University were selected. Predicted and observed 5-year overall survival (OS) for both v3.0 and v2.2 were compared. Discrimination was compared using receiver-operator curves and DeLong test. Calibration was evaluated using calibration plots and chi-squared test. A difference greater than 5% was deemed clinically relevant.

RESULTS

A total of 5424 patients were included, with median follow-up time of 58 months (IQR 38-89 months). Compared to v2.2, v3.0 did not show improved discriminatory accuracy for 5-year OS (AUC: 0.756 vs 0.771), same as ER-positive and ER-negative patients. However, calibration was significantly improved in v3.0, with predicted 5-year OS deviated from observed by -2.0% for the entire cohort, -2.9% for ER-positive and -0.0% for ER-negative patients, compared to -7.3%, -4.7% and -13.7% in v2.2. In v3.0, 5-year OS was underestimated by 9.0% for patients older than 75 years, and 5.8% for patients with micrometastases. Patients with distant metastases postdiagnosis was overestimated by 10.6%.

CONCLUSIONS

PREDICT v3.0 reliably predicts 5-year OS for the majority of Chinese patients with breast cancer. PREDICT v3.0 significantly improved the predictive accuracy for ER-negative groups. Furthermore, caution is advised when interpreting 5-year OS for patients aged over 70, those with micrometastases or metastases postdiagnosis.

SHG Fiberscopy Assessment of Collagen Morphology and Its Potential for Breast Cancer Optical Histology

OBJECTIVE

This study is to investigate the feasibility of our recently developed nonlinear fiberscope for label-free in situ breast tumor detection and lymph node status assessment based on second harmonic generation (SHG) imaging of fibrillar collagen matrix with histological details. The long-term goal is to improve the current biopsy-based cancer paradigm with reduced sampling errors.

METHODS

In this pilot study we undertook retrospective SHG imaging study of ex vivo invasive ductal carcinoma human biopsy tissue samples, and carried out quantitative image analysis to search for collagen structural signatures that are associated with the malignance of breast cancer.

RESULTS

SHG fiberscopy image-based quantitative assessment of collagen fiber morphology reveals that: 1) cancerous tissues contain generally less extracellular collagen fibers compared with tumor-adjacent normal tissues, and 2) collagen fibers in lymph node positive biopsies are more aligned than lymph node negative counterparts.

CONCLUSION/SIGNIFICANCE

The results demonstrate the promising potential of our SHG fiberscope for in situ breast tumor detection and lymph node involvement assessment and for offering real-time guidance during ongoing tissue biopsy.

Setting-up a training programme for intraoperative molecular imaging and sentinel node mapping: how to teach? How to learn?

BACKGROUND

The current expansion of image-guided surgery is closely related to the role played by radio-guided surgery in supporting the sentinel node (SN) procedure during more than three decades. The so-called triple approach (lymphoscintigraphy, gamma probe detection and blue dye) was not only essential in the seminal validation of the SN procedure but also a first collective learning effort based on skill transfer and outcome-related evaluation which laid the fundaments to delineate the field of intraoperative molecular imaging (IMI) based on a similar multimodality approach and multidisciplinary practice.

METHODS

These elements are also becoming valid in the current incorporation of SPECT/CT and PET/CT to existing and new protocols of IMI procedures and SN mapping concerning other clinical applications. On the other hand, there is a growing tendency to combine novel modern technologies in an allied role with gamma guidance in the operating room following the development of hybrid tracers and multimodal detection approaches. Against this background, learning initiatives are required for professionals working in this area.

RESULTS

This objective has led to a group of European practitioners with large experience in SN mapping and IMI applications to give shape to a programme made up out of specific learning modules aimed to be used as a conductive thread in peripherical or centralised training instances concerning the topic.

CONCLUSION

The presented work, written as a tutorial review, is placed in an available prior-art context and is primarily aimed at medical and paramedical practitioners as well as at hardware and software developers.

The Prognostic Value of Serum Albumin to Globulin Ratio in Patients with Breast Cancer: A Retrospective Study

Objective

This study examined the potential risk value of the serum albumin to globulin ratio (AGR) in patients with breast cancer (BC).

Methods

This study employed a retrospective design, enrolling 332 patients with BC and 38 patients without BC treated at Taizhou People's Hospital between September 2015 and May 2021. Multivariate Cox proportional hazard regression models were used to identify potential risk factors. A prognostic nomogram was developed based on the multivariate analyses. The receiver operating characteristic curve determined the optimal cutoff value for AGR.

Results

The results indicated a statistically significant decrease in AGR among patients with BC. Significant disparities were observed in globulin and AGR levels between the two cohorts. AGR was significantly associated with tumor size and stage, with a marked decline in advanced stages of BC. Additionally, AGR and aspartate transaminase/Alanine aminotransferase (AST/ALT) emerged as significant diagnostic indicators for invasive carcinoma and advanced stages (II-IV) of BC. Specifically, AGR exhibited an area under the curve of 0.645 (P < 0.003), highlighting the discriminatory capacity of serum globulin levels in distinguishing between BC and non-BC cohorts.

Conclusions

The AGR, routinely assessed due to its simplicity, objectivity, and cost-effectiveness, holds promise as a potential risk factor for BC and may have practical implications in clinical settings.

Guidelines of the Brazilian Society of Surgical Oncology for anatomopathological, immunohistochemical, and molecular testing in female tumors

INTRODUCTION

Precision medicine has revolutionized oncology, providing more personalized diagnosis, treatment, and monitoring for patients with cancer. In the context of female-specific tumors, such as breast, ovarian, endometrial, and cervical cancer, proper tissue collection and handling are essential for obtaining tissue, immunohistochemical (IHC), and molecular data to guide therapeutic decisions.

OBJECTIVES

To establish guidelines for the collection and handling of tumor tissue, to enhance the quality of samples for histopathological, IHC, genomic, and molecular analyses. These guidelines are fundamental in informing therapeutic decisions in cancer treatment.

METHOD

The guidelines were developed by a multidisciplinary panel of renowned specialists between June 12, 2013 and February 12, 2024. Initially, the panel deliberated on critical and controversial topics related to conducting precision medicine studies focusing on female tumors. Subsequently, 22 pivotal topics were identified within the framework and assigned to groups. These groups reviewed relevant literature and drafted preliminary recommendations. Following this, the recommendations were reviewed by the coordinators and received unanimous approval. Finally, the groups made the final adjustments, classified the level of evidence, and ranked the recommendations.

CONCLUSION

The collection of surgical samples requires minimum quality standards to enable histopathological, IHC, genomic, and molecular analyses. These analyses provide crucial data for informing therapeutic decisions, significantly impacting potential survival gains for patients with female tumors.

Joint EANM-SNMMI guideline on the role of 2-[18F]FDG PET/CT in no special type breast cancer : (endorsed by the ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA)

INTRODUCTION

There is much literature about the role of 2-[18F]FDG PET/CT in patients with breast cancer (BC). However, there exists no international guideline with involvement of the nuclear medicine societies about this subject.

PURPOSE

To provide an organized, international, state-of-the-art, and multidisciplinary guideline, led by experts of two nuclear medicine societies (EANM and SNMMI) and representation of important societies in the field of BC (ACR, ESSO, ESTRO, EUSOBI/ESR, and EUSOMA).

METHODS

Literature review and expert discussion were performed with the aim of collecting updated information regarding the role of 2-[18F]FDG PET/CT in patients with no special type (NST) BC and summarizing its indications according to scientific evidence. Recommendations were scored according to the National Institute for Health and Care Excellence (NICE) criteria.

RESULTS

Quantitative PET features (SUV, MTV, TLG) are valuable prognostic parameters. In baseline staging, 2-[18F]FDG PET/CT plays a role from stage IIB through stage IV. When assessing response to therapy, 2-[18F]FDG PET/CT should be performed on certified scanners, and reported either according to PERCIST, EORTC PET, or EANM immunotherapy response criteria, as appropriate. 2-[18F]FDG PET/CT may be useful to assess early metabolic response, particularly in non-metastatic triple-negative and HER2+ tumours. 2-[18F]FDG PET/CT is useful to detect the site and extent of recurrence when conventional imaging methods are equivocal and when there is clinical and/or laboratorial suspicion of relapse. Recent developments are promising.

CONCLUSION

2-[18F]FDG PET/CT is extremely useful in BC management, as supported by extensive evidence of its utility compared to other imaging modalities in several clinical scenarios.

Implementation of the Targeted Axillary Dissection Procedure in Clinically Node-Positive Breast Cancer: A Retrospective Analysis

BACKGROUND

The targeted axillary dissection (TAD) procedure is used in clinically positive lymph node (cN+) breast cancer to assess whether pathological complete response (pCR) is achieved after neoadjuvant systemic therapy (NST) to decide on de-escalation of axillary lymph node dissection (ALND). In this study, we review the implementation of the TAD procedure in a large regional breast cancer center.

METHODS

All TAD procedures between 2016 and 2022 were reviewed. The TAD procedure consists of marking pre-NST the largest suspected metastatic lymph node(s) using a radioactive I-125 seed. During surgery, the marked node was excised together with a sentinel node procedure. Axillary therapy (ALND, axillary radiotherapy, or nothing) recommendations were based on the amount of suspected positive axillary lymph nodes (ALNs < 4 or ≥ 4) pre-NST and if pCR was achieved after NST.

RESULTS

A total of 312 TAD procedures were successfully performed in 309 patients. In 134 (43%) cases, pCR of the TAD lymph nodes were achieved. Per treatment protocol, 43 cases (14%) did not receive any axillary treatment, 218 cases (70%) received adjuvant axillary radiotherapy, and 51 cases (16%) underwent an ALND. During a median follow-up of 2.8 years, 46 patients (14%) developed recurrence, of which 11 patients (3.5%) had axillary recurrence.

CONCLUSIONS

Introduction of the TAD procedure has resulted in a reduction of 84% of previously indicated ALNDs. Moreover, 18% of cases did not receive adjuvant axillary radiotherapy. These data show that implementation of de-escalation axillary treatment with the TAD procedure appeared to be successful.

Circulating C-reactive protein levels as a prognostic biomarker in breast cancer across body mass index groups

Obesity and systemic inflammation are associated with breast cancer (BC) outcomes. Systemic inflammation is increased in obesity. We examined the association between C-reactive protein (CRP) and disease-free survival (DFS) and overall survival (OS) overall, and according to body mass index (BMI). We assembled a cohort of women with BC (stage I-III) seen at Aarhus University Hospital between 2010 and 2020 who donated blood at BC diagnosis (N = 2673). CRP levels were measured and divided into quartiles. We followed patients from surgery to recurrence, contralateral BC, other malignancy, death, emigration, or end-of-follow-up. We used Cox regression to estimate hazard ratios (HRs) with 95% confidence intervals (95% CIs) to compare outcomes across CRP quartiles, overall and stratified by BMI (normal-weight (18.5 ≤ BMI < 25 kg/m2), overweight (25 ≤ BMI < 30 kg/m2), and obesity (BMI ≥ 30 kg/m2)). During follow-up, 368 events (212 recurrences, 38 contralateral BCs, and 118 deaths) occurred (median follow-up 5.55 years). For DFS, high CRP (CRP ≥ 3.19 mg/L) was associated with an increased risk of events (HRadj:1.62 [95% CI = 1.14-2.28]). In BMI-stratified analyses, high CRP was associated with elevated risk of events in normal-weight and overweight (HRadj:1.70 [95% CI = 1.09-2.66]; HRadj:1.75 [95% CI = 1.08-2.86]), but in obesity, the estimate was less precise (HRadj:1.73 [95% CI = 0.78-3.83]). For OS, high CRP was associated with increased risk of death (HRadj:2.47 [95% CI = 1.62-3.76]). The association was strong in normal-weight and overweight (HRadj:3.66 [95% CI = 1.95-6.87]; HRadj:1.92 [95% CI = 1.06-3.46]), but less clear in obesity (HRadj:1.40 [95% CI = 0.64-3.09]). To sum up, high CRP levels at BC diagnosis were associated with inferior prognosis in early BC irrespective of BMI, although less clear in patients with obesity.

Predictive efficacy of the preoperative neutrophil-lymphocyte ratio in lymph node metastasis of cN0 hormone receptor-positive breast cancer

Breast cancer, as the most common cancer, has surpassed lung cancer worldwide. The neutrophil-to-lymphocyte ratio (NLR) has been linked to the onset of cancer and its prognosis in recent studies. However, quite a few studies have shown that there is a link between NLR and lymph node metastases in cN0 hormone receptor-positive (HR(+)) breast cancer. The purpose of this study was to evaluate the correlation between NLR and lymph node metastases in cN0 HR(+) breast cancer patients. From January 2012 to January 2022, 220 patients with cN0 HR(+) invasive breast cancers were enrolled in this study. The relationship between NLR and pathological data was statistically examined. The receiver operating characteristic (ROC) curve was used to determine the optimal cutoff of NLR, a chi-squared test was used for the univariate analysis, and logistic analysis was used for the multivariate analysis. The NLR had an optimal cutoff of 2.4 when the Jorden index was at a maximum. Patients with axillary lymph node metastases had a higher NLR (P < 0.05). A Univariate analysis showed that there were significant differences in cN0 HR(+) breast cancer with axillary lymph node metastasis among different clinical stages, histological grades, Ki-67 levels, tumor sizes, and NLR levels (P < 0.05). Clinical stage, tumor size, and NLR were found to be independent risk factors for lymph node metastases in multifactorial analysis. In cN0 HR(+) breast cancer, NLR is an independent risk factor for lymph node metastases. An NLR ≥ 2.4 indicates an increased probability of lymph node metastases. An elevated preoperative NLR has a high predictive value for axillary lymph node metastases.

Triple-negative breast cancer survival prediction: population-based research using the SEER database and an external validation cohort

Introduction

Triple-negative breast cancer (TNBC) is linked to a poorer outlook, heightened aggressiveness relative to other breast cancer variants, and limited treatment choices. The absence of conventional treatment methods makes TNBC patients susceptible to metastasis. The objective of this research was to assess the clinical and pathological traits of TNBC patients, predict the influence of risk elements on their outlook, and create a prediction model to assist doctors in treating TNBC patients and enhancing their prognosis.

Methods

We included 23,394 individuals with complete baseline clinical data and survival information who were diagnosed with primary TNBC between 2010 and 2015 based on the SEER database. External validation utilised a group from The Affiliated Lihuili Hospital of Ningbo University. Independent risk factors linked to TNBC prognosis were identified through univariate, multivariate, and least absolute shrinkage and selection operator regression methods. These characteristics were chosen as parameters to develop 3- and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) nomogram models. Model accuracy was assessed using calibration curves, consistency indices (C-indices), receiver operating characteristic curves (ROCs), and decision curve analyses (DCAs). Finally, TNBC patients were divided into groups of high, medium, and low risk, employing the nomogram model for conducting a Kaplan-Meier survival analysis.

Results

In the training cohort, variables such as age at diagnosis, marital status, grade, T stage, N stage, M stage, surgery, radiation, and chemotherapy were linked to OS and BCSS. For the nomogram, the C-indices stood at 0.762, 0.747, and 0.764 in forecasting OS across the training, internal validation, and external validation groups, respectively. Additionally, the C-index values for the training, internal validation, and external validation groups in BCSS prediction stood at 0.793, 0.755, and 0.811, in that order. The findings revealed that the calibration of our nomogram model was successful, and the time-variant ROC curves highlighted its effectiveness in clinical settings. Ultimately, the clinical DCA showcased the prospective clinical advantages of the suggested model. Furthermore, the online version was simple to use, and nomogram classification may enhance the differentiation of TNBC prognosis and distinguish risk groups more accurately.

Conclusion

These nomograms are precise tools for assessing risk in patients with TNBC and forecasting survival. They can help doctors identify prognostic markers and create more effective treatment plans for patients with TNBC, providing more accurate assessments of their 3- and 5-year OS and BCSS.

Prediction of the axillary lymph-node metastatic burden of breast cancer by 18F-FDG PET/CT-based radiomics

BACKGROUND

The axillary lymph-node metastatic burden is closely associated with treatment decisions and prognosis in breast cancer patients. This study aimed to explore the value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography (CT)-based radiomics in combination with ultrasound and clinical pathological features for predicting axillary lymph-node metastatic burden in breast cancer.

METHODS

A retrospective analysis was conducted and involved 124 patients with pathologically confirmed early-stage breast cancer who had undergone 18F-FDG PET/CT examination. The ultrasound, PET/CT, and clinical pathological features of all patients were analysed, and radiomic features from PET images were extracted to establish a multi-parameter predictive model.

RESULTS

The ultrasound lymph-node positivity rate and PET lymph-node positivity rate in the high nodal burden group were significantly higher than those in the low nodal burden group (χ2 = 19.867, p < 0.001; χ2 = 33.025, p < 0.001). There was a statistically significant difference in the PET-based radiomics score (RS) for predicting axillary lymph-node burden between the high and low lymph-node burden groups. (-1.04 ± 0.41 vs. -1.47 ± 0.41, t = -4.775, p < 0.001). The ultrasound lymph-node positivity (US_LNM) (odds ratio [OR] = 3.264, 95% confidence interval [CI] = 1.022-10.423), PET lymph-node positivity (PET_LNM) (OR = 14.242, 95% CI = 2.960-68.524), and RS (OR = 5.244, 95% CI = 3.16-20.896) are all independent factors associated with high lymph-node burden (p < 0.05). The area under the curve (AUC) of the multi-parameter (MultiP) model was 0.895, which was superior to those of US_LNM, PET_LNM, and RS models (AUC = 0.703, 0.814, 0.773, respectively), with statistically significant differences (Z = 2.888, 3.208, 3.804, respectively; p = 0.004, 0.002, < 0.001, respectively). Decision curve analysis indicated that the MultiP model provided a higher net benefit for all patients.

CONCLUSION

A MultiP model based on PET-based radiomics was able to effectively predict axillary lymph-node metastatic burden in breast cancer.

TRIAL REGISTRATION

This study was registered with ClinicalTrials.gov (registration number: NCT05826197) on May 7, 2023.

Comparison of the efficacy of taxanes with carboplatin and anthracyclines with taxanes in neoadjuvant chemotherapy for stage II-III triple negative breast cancer: a retrospective analysis

PURPOSE

The neoadjuvant chemotherapy (NACT) regimen for triple negative breast cancer (TNBC) primarily consists of anthracyclines and taxanes, and the addition of platinum-based drugs can further enhance the efficacy. However, it is also accompanied by more adverse events, and considering the potential severe and irreversible toxicity of anthracyclines, an increasing number of studies are exploring nonanthracycline regimens that combine taxanes and platinum-based drugs.

METHODS

The retrospective study included 273 stage II-III TNBC patients who received NACT. The AT group, consisting of 195 (71.4%) patients, received a combination of anthracyclines and taxanes, while the TCb group, consisting of 78 (28.6%) patients, received a combination of taxanes and carboplatin. Logistic regression analysis was performed to evaluate the factors influencing pathological complete response (pCR) and residual cancer burden (RCB). The log-rank test was used to assess the differences in event-free survival (EFS) and overall survival (OS) among the different treatment groups. Cox regression analysis was conducted to evaluate the factors influencing EFS and OS.

RESULTS

After NACT and surgery, the TCb group had a higher rate of pCR at 44.9%, as compared to the AT group at 31.3%. The difference between the two groups was 13.6% (OR = 0.559, 95% CI 0.326-0.959, P = 0.035). The TCb group had a 57.7% rate of RCB 0-1, which was higher than the AT group's rate of 42.6%. The difference between the two groups was 15.1% (OR = 0.543, 95% CI 0.319-0.925, P = 0.024), With a median follow-up time of 40 months, the TCb group had better EFS (log-rank, P = 0.014) and OS (log-rank, P = 0.040) as compared to the AT group. Clinical TNM stage and RCB grade were identified as independent factors influencing EFS and OS, while treatment group was identified as an independent factor influencing EFS, with a close-to-significant impact on OS.

CONCLUSION

In stage II-III triple TNBC patients, the NACT regimen combining taxanes and carboplatin yields higher rates of pCR and significant improvements in EFS and OS as compared to the regimen combining anthracyclines and taxanes.

The predictive value of systemic immune-inflammatory markers before and after treatment for pathological complete response in patients undergoing neoadjuvant therapy for breast cancer: a retrospective study of 1994 patients

PURPOSE

Systemic immune-inflammatory markers have a certain predictive role in pathological complete response (pCR) after neoadjuvant treatment (NAT) in breast cancer. However, there is a lack of research exploring the predictive value of markers after treatment.

METHODS

This retrospective study collected data from 1994 breast cancer patients who underwent NAT. Relevant clinical and pathological characteristics were included, and pre- and post-treatment complete blood cell counts were evaluated to calculate four systemic immune-inflammatory markers: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammation index (SII). The optimal cutoff values for these markers were determined using ROC curves, and patients were classified into high-value and low-value groups based on these cutoff values. Univariate and multivariate logistic regression analyses were conducted to analyze factors influencing pCR. The factors with independent predictive value were used to construct a nomogram.

RESULTS

After NAT, 383 (19.2%) patients achieved pCR. The area under the ROC curve is generally larger for post-treatment markers compared to pre-treatment markers. Pre-treatment NLR and PLR, as well as post-treatment LMR and SII, were identified as independent predictive factors for pCR, along with Ki-67, clinical tumor stage, clinical lymph node stage, molecular subtype, and clinical response. Higher pre-NLR (OR = 1.320; 95% CI 1.016-1.716; P = 0.038), pre-PLR (OR = 1.474; 95% CI 1.058-2.052; P = 0.022), post-LMR (OR = 1.532; 95% CI 1.175-1.996; P = 0.002), and lower post-SII (OR = 0.596; 95% CI 0.429-0.827; P = 0.002) are associated with a higher likelihood of achieving pCR. The established nomogram had a good predictive performance with an area under the ROC curve of 0.754 (95% CI 0.674-0.835).

CONCLUSION

Both pre- and post-treatment systemic immune-inflammatory markers have a significant predictive role in achieving pCR after NAT in breast cancer patients. Indeed, it is possible that post-treatment markers have stronger predictive ability compared to pre-treatment markers.

ACR Appropriateness Criteria® Imaging of Invasive Breast Cancer

As the proportion of women diagnosed with invasive breast cancer increases, the role of imaging for staging and surveillance purposes should be determined based on evidence-based guidelines. It is important to understand the indications for extent of disease evaluation and staging, as unnecessary imaging can delay care and even result in adverse outcomes. In asymptomatic patients that received treatment for curative intent, there is no role for imaging to screen for distant recurrence. Routine surveillance with an annual 2-D mammogram and/or tomosynthesis is recommended to detect an in-breast recurrence or a new primary breast cancer in women with a history of breast cancer, and MRI is increasingly used as an additional screening tool in this population, especially in women with dense breasts. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Decoding the Prevalent High-Risk Breast Cancers: Demographics, Pathological, Imaging Insights, and Long-Term Outcome

Objective: To investigate the features and outcomes of breast cancer in high-risk subgroups. Materials and Methods: REB approved an observational study of women diagnosed with breast cancer from 2010 to 2019. Three radiologists, using the BI-RADS lexicon, blindly reviewed mammogram and MRI screenings without a washout period. Consensus was reached with 2 additional reviewers. Inter-rater agreement was measured by Fleiss Kappa. Statistical analysis included Mann-Whitney U, Chi-square tests for cohort analysis, and Kaplan-Meier for survival rates, with a Cox model for comparative analysis using gene mutation as a reference. Results: The study included 140 high-risk women, finding 155 malignant lesions. Significant age differences noted: chest radiation therapy (median age 44, IQR: 37.0-46.2), gene mutation (median age 49, IQR: 39.8-58.0), and familial risk (median age 51, IQR: 44.5-56.0) (P = .007). Gene mutation carriers had smaller (P = .01), higher-grade tumours (P = .002), and more triple-negative ER- (P = .02), PR- (P = .002), and HER2- (P = .02) cases. MRI outperformed mammography in all subgroups. Substantial to near-perfect inter-rater agreement observed. Over 10 years, no deaths occurred in chest radiation group, with no significant survival difference between gene mutation and familial risk groups, HR = 0.93 (95% CI: 0.27, 3.26), P = .92. Conclusion: The study highlights the importance of age and specific tumour characteristics in identifying high-risk breast cancer subgroups. MRI is confirmed as an effective screening tool. Despite the aggressive nature of cancers in gene mutation carriers, early detection is crucial for survival outcomes. These insights, while necessitating further validation with larger studies, advocate for a move toward personalized medical care, strengthening the existing healthcare guidelines.

Forget Me Not: Incidental Findings on Breast MRI

With the growing utilization and expanding role of breast MRI, breast imaging radiologists may encounter an increasing number of incidental findings beyond the breast and axilla. Breast MRI encompasses a large area of anatomic coverage extending from the lower neck to the upper abdomen. While most incidental findings on breast MRI are benign, identifying metastatic disease can have a substantial impact on staging, prognosis, and treatment. Breast imaging radiologists should be familiar with common sites, MRI features, and breast cancer subtypes associated with metastatic disease to assist in differentiating malignant from benign findings. Furthermore, detection of malignancies of nonbreast origin as well as nonmalignant, but clinically relevant, incidental findings can significantly impact clinical management and patient outcomes. Breast imaging radiologists should consistently follow a comprehensive search pattern and employ techniques to improve the detection of these important incidental findings.

Identification of the new molecular subtypes related to inflammation in breast cancer

Breast cancer is a prevalent ailment among women, and the inflammatory response plays a crucial role in the management and prediction of breast cancer (BRCA). However, the new subtypes based on inflammation in BRCA research are still undefined. The databases including The Cancer Genome Atlas and gene expression omnibus were utilized to gather clinical data and somatic mutation information for approximately 1069 BRCA patients. Through Consensus Clustering, novel subtypes linked to inflammation were identified. A comparative analysis was conducted on the prognosis, and immune cell infiltration, and somatic mutation of the new subtypes. Additionally, an investigation into drug therapy and immunotherapy was conducted to distinguish high-risk individuals from low-risk ones. The findings of this investigation proposed the categorization of BRCA into innovative subtypes predicated on the inflammatory response and 6 key genes were a meaningful approach. Specifically, the low-, medium-, and high-inflammation subtypes exhibited varying degrees of association with clinicopathological features, tumor microenvironment, and prognosis. Notably, the high-inflammation subtype was characterized by a strong correlation with immunosuppressive microenvironments and a higher frequency of somatic mutations, which was an indication of poorer health. This study revealed that a brand-new classification could throw new light on the effective prognosis. The integration of multiple key genes was a new characterization that could promote more immunotherapy strategies and contribute to predicting the efficacy of the chemotherapeutic drugs.

Upgrade Rates of Variant Lobular Carcinoma In Situ Compared to Classic Lobular Carcinoma In Situ Diagnosed in Core Needle Biopsies: A 10-Year Single Institution Retrospective Study

The primary aim of this study was to determine the upgrade rates of variant lobular carcinoma in situ (V-LCIS, ie, combined florid [F-LCIS] and pleomorphic [P-LCIS]) compared with classic LCIS (C-LCIS) when diagnosed on core needle biopsy (CNB). The secondary goal was to determine the rate of progression/development of invasive carcinoma on long-term follow-up after primary excision. After institutional review board approval, our institutional pathology database was searched for patients with "pure" LCIS diagnosed on CNB who underwent subsequent excision. Radiologic findings were reviewed, radiologic-pathologic (rad-path) correlation was performed, and follow-up patient outcome data were obtained. One hundred twenty cases of LCIS were identified on CNB (C-LCIS = 97, F-LCIS = 18, and P-LCIS = 5). Overall upgrade rates after excision for C-LCIS, F-LCIS, and P-LCIS were 14% (14/97), 44% (8/18), and 40% (2/5), respectively. Of the total cases, 79 (66%) were deemed rad-path concordant. Of these, the upgrade rate after excision for C-LCIS, F-LCIS, and P-LCIS was 7.5% (5 of 66), 40% (4 of 10), and 0% (0 of 3), respectively. The overall upgrade rate for V-LCIS was higher than for C-LCIS (P = .004), even for the cases deemed rad-path concordant (P value: .036). Most upgraded cases (23 of 24) showed pT1a disease or lower. With an average follow-up of 83 months, invasive carcinoma in the ipsilateral breast was identified in 8/120 (7%) cases. Six patients had died: 2 of (contralateral) breast cancer and 4 of other causes. Because of a high upgrade rate, V-LCIS diagnosed on CNB should always be excised. The upgrade rate for C-LCIS (even when rad-path concordant) is higher than reported in many other studies. Rad-path concordance read, surgical consultation, and individualized decision making are recommended for C-LCIS cases. The risk of developing invasive carcinoma after LCIS diagnosis is small (7% with ∼7-year follow-up), but active surveillance is required to diagnose early-stage disease.

Efficacy of tyrosine kinase inhibitors examined by a combination of Raman micro-spectroscopy and a deep wavelet scattering-based multivariate analysis framework

HER2 is a crucial therapeutic target in breast cancer, and the survival rate of breast cancer patients has increased because of this receptor's inhibition. However, tumors have shown resistance to this therapeutic strategy due to oncogenic mutations that decrease the binding of several HER2-targeted drugs, including lapatinib, and confer resistance to this drug. Neratinib can overcome this drug resistance and effectively inhibit HER2 signaling and tumor growth. In the present study, we examined the efficacy of lapatinib and neratinib using breast cancer cells by Raman microscopy combined with a deep wavelet scattering-based multivariate analysis framework. This approach discriminated between control cells and drug-treated cells with high accuracy, compared to classical principal component analysis. Both lapatinib and neratinib induced changes in the cellular biochemical composition. Furthermore, the Raman results were compared with the results of several in vitro assays. For instance, drug-treated cells exhibited (i) inhibition of ERK and AKT phosphorylation, (ii) inhibition of cellular proliferation, (iii) cell-cycle arrest, and (iv) apoptosis as indicated by western blotting, real-time cell analysis (RTCA), cell-cycle analysis, and apoptosis assays. Thus, the observed Raman spectral changes are attributed to cell-cycle arrest and apoptosis. The results also indicated that neratinib is more potent than lapatinib. Moreover, the uptake and distribution of lapatinib in cells were visualized through its label-free marker bands in the fingerprint region using Raman spectral imaging. These results show the prospects of Raman microscopy in drug evaluation and presumably in drug discovery.

Comparison of Clinicopathological Features of Pleomorphic and Invasive Lobular Breast Carcinomas

PURPOSE

Accounting for about 15% of invasive lobular carcinomas and 1% of breast carcinomas, pleomorphic lobular carcinoma is known to be a rare histological subtype of invasive lobular carcinoma. Yet, it is more aggressive and produces a worse prognosis than other breast cancers. Ultimately, the present study compares the clinicopathological features of pleomorphic and invasive lobular breast carcinomas.

METHODS

In the study, we retrospectively evaluated the data of 262 patients with histological subtypes of classical and pleomorphic lobular cancers having been recruited for surgical operations. After resorting to Kolmogorov-Smirnov and Shapiro-Wilk tests to check the normality of distribution, the categorical and continuous variables were compared between the groups using the chi-square test and independent samples t test, respectively. In all analyses, we considered a P-value of <.05 to be statistically significant.

RESULTS

Our findings revealed that the groups with lobular and pleomorphic groups significantly differed by Ki-67 value, estrogen receptor negativity, grade, multicentricity, multifocality, surgical margin positivity, completion mastectomy, and metachronous contralateral tumor (P < .05).

CONCLUSION

We discovered that pleomorphic type was associated with higher grades, estrogen receptor negativity, and Ki-67 expression. The incidence of metachronous breast cancer was high in the pleomorphic group, which may be a noteworthy finding to be considered in follow-ups. In addition, the high rates of multicentricity and multifocality of tumors in the pleomorphic group may be associated with increased surgical margin positivity and a higher likelihood of mastectomy. In a nutshell, our findings may guide patients and surgeons regarding the type of intervention and reconstruction options to be adopted in prospective surgeries.

Assessing of case-cohort design: a case study for breast cancer patients in Xinjiang, China

Objective

To assess the effectiveness and clinical value of case-cohort design and determine prognostic factors of breast cancer patients in Xinjiang on the basis of case-cohort design.

Methods

The survival data with different sample characteristics were simulated by using Cox proportional risk models. To evaluate the effectiveness for the case-cohort, entire cohort, and simple random sampling design by comparing the mean, coefficient of variation, etc., of covariate parameters. Furthermore, the prognostic factors of breast cancer patients in Xinjiang were determined based on case-cohort sampling designs. The models were comprehensively evaluated by likelihood ratio test, the area under the receiver operating characteristic curve (AUC), and Akaike Information Criterion (AIC).

Results

In a simulations study, the case-cohort design shows better stability and improves the estimation efficiency when the censored rate is high. In the breast cancer data, molecular subtypes, T-stage, N-stage, M-stage, types of surgery, and postoperative chemotherapy were identified as the prognostic factors of patients in Xinjiang. These models based on the different sampling designs both passed the likelihood ratio test (p<0.05). Moreover, the model constructed under the case-cohort design had better fitting effect (AIC=3,999.96) and better discrimination (AUC=0.807).

Conclusion

Simulations study confirmed the effectiveness of case-cohort design and further determined the prognostic factors of breast cancer patients in Xinjiang based on this design, which presented the practicality of case-cohort design in actual data.

Convergence between helminths and breast cancer: intratumoral injection of the excretory/secretory antigens of the human parasite Toxocara canis (EST) increase lung macro and micro metastasis

Introduction

Worldwide, breast cancer is the most important cancer in incidence and prevalence in women. Different risk factors interact to increase the probability of developing it. Biological agents such as helminth parasites, particularly their excretory/secretory antigens, may play a significant role in tumor development. Helminths and their antigens have been recognized as inducers or promoters of cancer due to their ability to regulate the host's immune response. Previously in our laboratory, we demonstrated that chronic infection by Toxocara canis increases the size of mammary tumors, affecting the systemic response to the parasite. However, the parasite does not invade the tumor, and we decided to study if the excretion/secretion of antigens from Toxocara canis (EST) can affect the progression of mammary tumors or the pathophysiology of cancer which is metastasis. Thus, this study aimed to determine whether excretion/secretion T. canis antigens, injected directly into the tumor, affect tumor growth and metastasis.

Methods

We evaluated these parameters through the monitoring of the intra-tumoral immune response.

Results

Mice injected intratumorally with EST did not show changes in the size and weight of the tumors; although the tumors showed an increased microvasculature, they did develop increased micro and macro-metastasis in the lung. The analysis of the immune tumor microenvironment revealed that EST antigens did not modulate the proportion of immune cells in the tumor, spleen, or peripheral lymph nodes. Macroscopic and microscopic analyses of the lungs showed increased metastasis in the EST-treated animals compared to controls, accompanied by an increase in VEGF systemic levels.

Discussion

Thus, these findings showed that intra-tumoral injection of T. canis EST antigens promote lung metastasis through modulation of the tumor immune microenvironment.

Development of a Multi-Parametric ultrasonography nomogram for prediction of invasiveness in ductal carcinoma in situ

OBJECTIVE

To investigate the independent risk variables associated with the potential invasiveness of ductal carcinoma in situ (DCIS) on multi-parametric ultrasonography, and further construct a nomogram for risk assessment.

METHODS

Consecutive patients from January 2017 to December 2022 who were suspected of having ductal carcinoma in situ (DCIS) based on magnetic resonance imaging or mammography were prospectively enrolled. Histopathological findings after surgical resection served as the gold standard. Grayscale ultrasound, Doppler ultrasound, shear wave elastography (SWE), and contrast-enhanced ultrasound (CEUS) examinations were preoperative performed. Binary logistic regression was used for multifactorial analysis to identify independent risk factors from multi-parametric ultrasonography. The correlation between independent risk factors and pathological prognostic markers was analyzed. The predictive efficacy of DCIS associated with invasiveness was assessed by logistic analysis, and a nomogram was established.

RESULTS

A total of 250 DCIS lesions were enrolled from 249 patients, comprising 85 pure DCIS and 165 DCIS with invasion (DCIS-IDC), of which 41 exhibited micro-invasion. The multivariate analysis identified independent risk factors for DCIS with invasion on multi-parametric ultrasonography, including image size (>2cm), Doppler ultrasound RI (≥0.72), SWE's Emax (≥66.4 kPa), hyper-enhancement, centripetal enhancement, increased surrounding vessel, and no contrast agent retention on CEUS. These factors correlated with histological grade, Ki-67, and human epidermal growth factor receptor 2 (HER2) (P < 0.1). The multi-parametric ultrasound approach demonstrated good predictive performance (sensitivity 89.7 %, specificity 73.8 %, AUC 0.903), surpassing single US modality or combinations with SWE or CEUS modalities. Utilizing these factors, a predictive nomogram achieved a respectable performance (AUC of 0.889) for predicting DCIS with invasion. Additionally, a separate nomogram for predicting DCIS with micro-invasion, incorporating independent risk factors such as RI (≥0.72), SWE's Emax (≥65.2 kPa), and centripetal enhancement, demonstrated an AUC of 0.867.

CONCLUSION

Multi-parametric ultrasonography demonstrates good discriminatory ability in predicting both DCIS with invasion and micro-invasion through the analysis of lesion morphology, stiffness, neovascular architecture, and perfusion. The use of a nomogram based on ultrasonographic images offers an intuitive and effective method for assessing the risk of invasion in DCIS. Although the nomogram is not currently considered a clinically applicable diagnostic tool due to its AUC being below the threshold of 0.9, further research and development are anticipated to yield positive outcomes and enhance its viability for clinical utilization.

Automated and reusable deep learning (AutoRDL) framework for predicting response to neoadjuvant chemotherapy and axillary lymph node metastasis in breast cancer using ultrasound images: a retrospective, multicentre study

Background

Previous deep learning models have been proposed to predict the pathological complete response (pCR) and axillary lymph node metastasis (ALNM) in breast cancer. Yet, the models often leveraged multiple frameworks, required manual annotation, and discarded low-quality images. We aimed to develop an automated and reusable deep learning (AutoRDL) framework for tumor detection and prediction of pCR and ALNM using ultrasound images with diverse qualities.

Methods

The AutoRDL framework includes a You Only Look Once version 5 (YOLOv5) network for tumor detection and a progressive multi-granularity (PMG) network for pCR and ALNM prediction. The training cohort and the internal validation cohort were recruited from Guangdong Provincial People's Hospital (GPPH) between November 2012 and May 2021. The two external validation cohorts were recruited from the First Affiliated Hospital of Kunming Medical University (KMUH), between January 2016 and December 2019, and Shunde Hospital of Southern Medical University (SHSMU) between January 2014 and July 2015. Prior to model training, super-resolution via iterative refinement (SR3) was employed to improve the spatial resolution of low-quality images from the KMUH. We developed three models for predicting pCR and ALNM: a clinical model using multivariable logistic regression analysis, an image model utilizing the PMG network, and a combined model that integrates both clinical and image data using the PMG network.

Findings

The YOLOv5 network demonstrated excellent accuracy in tumor detection, achieving average precisions of 0.880-0.921 during validation. In terms of pCR prediction, the combined modelpost-SR3 outperformed the combined modelpre-SR3, image modelpost-SR3, image modelpre-SR3, and clinical model (AUC: 0.833 vs 0.822 vs 0.806 vs 0.790 vs 0.712, all p < 0.05) in the external validation cohort (KMUH). Consistently, the combined modelpost-SR3 exhibited the highest accuracy in ALNM prediction, surpassing the combined modelpre-SR3, image modelpost-SR3, image modelpre-SR3, and clinical model (AUC: 0.825 vs 0.806 vs 0.802 vs 0.787 vs 0.703, all p < 0.05) in the external validation cohort 1 (KMUH). In the external validation cohort 2 (SHSMU), the combined model also showed superiority over the clinical and image models (0.819 vs 0.712 vs 0.806, both p < 0.05).

Interpretation

Our proposed AutoRDL framework is feasible in automatically predicting pCR and ALNM in real-world settings, which has the potential to assist clinicians in optimizing individualized treatment options for patients.

Funding

National Key Research and Development Program of China (2023YFF1204600); National Natural Science Foundation of China (82227802, 82302306); Clinical Frontier Technology Program of the First Affiliated Hospital of Jinan University, China (JNU1AF-CFTP-2022-a01201); Science and Technology Projects in Guangzhou (202201020022, 2023A03J1036, 2023A03J1038); Science and Technology Youth Talent Nurturing Program of Jinan University (21623209); and Postdoctoral Science Foundation of China (2022M721349).

miR-125 in Breast Cancer Etiopathogenesis: An Emerging Role as a Biomarker in Differential Diagnosis, Regenerative Medicine, and the Challenges of Personalized Medicine

Breast Cancer (BC) is one of the most common cancer types worldwide, and it is characterized by a complex etiopathogenesis, resulting in an equally complex classification of subtypes. MicroRNA (miRNA or miR) are small non-coding RNA molecules that have an essential role in gene expression and are significantly linked to tumor development and angiogenesis in different types of cancer. Recently, complex interactions among coding and non-coding RNA have been elucidated, further shedding light on the complexity of the roles these molecules fulfill in cancer formation. In this context, knowledge about the role of miR in BC has significantly improved, highlighting the deregulation of these molecules as additional factors influencing BC occurrence, development and classification. A considerable number of papers has been published over the past few years regarding the role of miR-125 in human pathology in general and in several types of cancer formation in particular. Interestingly, miR-125 family members have been recently linked to BC formation as well, and complex interactions (competing endogenous RNA networks, or ceRNET) between this molecule and target mRNA have been described. In this review, we summarize the state-of-the-art about research on this topic.

Prediction of a Multi-Gene Assay (Oncotype DX and Mammaprint) Recurrence Risk Group Using Machine Learning in Estrogen Receptor-Positive, HER2-Negative Breast Cancer-The BRAIN Study

This study aimed to develop a machine learning-based prediction model for predicting multi-gene assay (MGA) risk categories. Patients with estrogen receptor-positive (ER+)/HER2- breast cancer who had undergone Oncotype DX (ODX) or MammaPrint (MMP) were used to develop the prediction model. The development cohort consisted of a total of 2565 patients including 2039 patients tested with ODX and 526 patients tested with MMP. The MMP risk prediction model utilized a single XGBoost model, and the ODX risk prediction model utilized combined LightGBM, CatBoost, and XGBoost models through soft voting. Additionally, the ensemble (MMP + ODX) model combining MMP and ODX utilized CatBoost and XGBoost through soft voting. Ten random samples, corresponding to 10% of the modeling dataset, were extracted, and cross-validation was performed to evaluate the accuracy on each validation set. The accuracy of our predictive models was 84.8% for MMP, 87.9% for ODX, and 86.8% for the ensemble model. In the ensemble cohort, the sensitivity, specificity, and precision for predicting the low-risk category were 0.91, 0.66, and 0.92, respectively. The prediction accuracy exceeded 90% in several subgroups, with the highest prediction accuracy of 95.7% in the subgroup that met Ki-67 <20 and HG 1~2 and premenopausal status. Our machine learning-based predictive model has the potential to complement existing MGAs in ER+/HER2- breast cancer.

Decline in the Incidence of Distant Recurrence of Breast Cancer: A Population-Based Health Record Linkage Study, Australia 2001-2016

BACKGROUND

We investigated differences in cumulative incidence of first distant recurrence (DR) following non-metastatic breast cancer over a time period when new adjuvant therapies became available in Australia.

METHODS

We conducted a health record linkage study of females with localized (T1-3N0) or regional (T4 or N+) breast cancer in the New South Wales Cancer Registry in 2001 to 2002 and 2006 to 2007. We linked cancer registry records with administrative records from hospitals, dispensed medicines, radiotherapy services, and death registrations to estimate the 9-year cumulative incidence of DR and describe use of adjuvant treatment.

RESULTS

The study included 13,170 women (2001-2002 n = 6,338, 2006-2007 n = 6,832). The 9-year cumulative incidence of DR was 3.6% [95% confidence interval (CI), 2.3%-4.9%] lower for 2006-2007 diagnoses (15.0%) than 2001-2002 (18.6%). Differences in the annual hazard of DR between cohorts were largest in year two. DR incidence declined for localized and regional disease. Decline was largest for ages <40 years (absolute difference, 14.4%; 95% CI, 8.3%-20.6%), whereas their use of adjuvant chemotherapy (2001-2002 49%, 2006-2007 75%) and HER2-targeted therapy (2001-2002 0%, 2006-2007 16%) increased. DR did not decline for ages ≥70 years (absolute difference, 0.9%; 95% CI, -3.6%-1.8%) who had low use of adjuvant chemotherapy and HER2-targeted therapy.

CONCLUSIONS

This whole-of-population study suggests that DR incidence declined over time. Decline was largest for younger ages, coinciding with changes to adjuvant breast cancer therapy.

IMPACT

Study findings support the need for trials addressing questions relevant to older people and cancer registry surveillance of DR to inform cancer control programs.

A new methodology to predict the oncotype scores based on clinico-pathological data with similar tumor profiles

PURPOSE

The Oncotype DX (ODX) test is a commercially available molecular test for breast cancer assay that provides prognostic and predictive breast cancer recurrence information for hormone positive, HER2-negative patients. The aim of this study is to propose a novel methodology to assist physicians in their decision-making.

METHODS

A retrospective study between 2012 and 2020 with 333 cases that underwent an ODX assay from three hospitals in the Bourgogne Franche-Comté region (France) was conducted. Clinical and pathological reports were used to collect the data. A methodology based on distributional random forest was developed to predict the ODX score classes (ODX [Formula: see text] and ODX [Formula: see text]) using 9 clinico-pathological characteristics. This methodology can be used particularly to identify the patients of the training cohort that share similarities with the new patient and to predict an estimate of the distribution of the ODX score.

RESULTS

The mean age of participants is 56.9 years old. We have correctly classified [Formula: see text] of patients in low risk and [Formula: see text] of patients in high risk. The overall accuracy is [Formula: see text]. The proportion of low risk correct predicted value (PPV) is [Formula: see text]. The percentage of high risk correct predicted value (NPV) is approximately [Formula: see text]. The F1-score and the Area Under Curve (AUC) are of 0.87 and 0.759, respectively.

CONCLUSION

The proposed methodology makes it possible to predict the distribution of the ODX score for a patient. This prediction is reinforced by the determination of a family of known patients with follow-up of identical scores. The use of this methodology with the pathologist's expertise on the different histological and immunohistochemical characteristics has a clinical impact to help oncologist in decision-making regarding breast cancer therapy.

Prognostic factors and benefit populations of ovarian function suppression in premenopausal HR+/HER2+ early-stage breast cancer patients who received trastuzumab: Evidence from a real-world study with long-term follow-up

BACKGROUND

Hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-positive (HER2+) breast cancer exhibits considerable heterogeneity, and it is of great interest whether patients with premenopausal HR+/HER2+ breast cancer treated with trastuzumab can benefit from ovarian function suppression (OFS) therapy similarly to HR+/HER2- breast cancer. Here, we conducted a real-world study in this population to identify both who would derive substantial benefits from the addition of OFS and clinicopathological factors with potential prognostic value.

METHODS

Multicenter data from 253 premenopausal patients with HR+/HER2+ early-stage breast cancer who received trastuzumab from October 2009 to October 2018 were retrospectively included. The Kaplan-Meier method was used for survival analysis, while the log-rank test was used to compare the survival rates. Univariate and multifactor Cox regression analyses were performed to analyze the independent risk factors affecting invasive disease-free survival (IDFS).

RESULTS

After a median follow-up of 98.50 months, compared with tamoxifen/toremifene alone, tamoxifen/toremifene/aromatase inhibitors plus OFS demonstrated significant benefits in the overall study population (HR = 0.289, 95% CI: 0.100-0.835, p = 0.022, 8-year IDFS rate: 90.78% vs. 95.54%), especially in the lymph node-positive subgroup and age ≤40 years subgroup. Age ≤40 years, histological grade >2, lymph node involvement, PR ≤50%, and tamoxifen alone were independent prognostic factors.

CONCLUSIONS

For premenopausal HR+ breast cancer patients, HER2 positivity alone is an indication for the addition of OFS in adjuvant endocrine therapy. Age, histological grade, lymph node status, the expression of PR, and OFS treatment were independent prognostic factors in this population.

Association of the m6 A reader IGF2BP3 with tumor progression and brain-specific metastasis in breast cancer

BACKGROUND

This study aimed to determine the role of insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), an N6 -methyladinosine reader, in the progression and distant metastasis of breast cancer.

METHODS

IGF2BP3 expression was assessed in 152 pairs of breast cancer and adjacent normal tissue (ANT) by real-time quantitative polymerase chain reaction and in 561 cases of breast cancer and 163 cases of ANT by immunohistochemistry. Survival curves were estimated using the Kaplan-Meier method and then compared statistically using the log-rank test. The prognostic role of IGF2BP3 was determined by Cox regression analysis.

RESULTS

Analysis of public gene data sets revealed that IGF2PB3 predicted distant metastasis in breast cancer and was highly correlated with brain metastasis. In the clinical retrospective cohort, the positive rate of IGF2BP3 increased gradually with breast cancer progression. Positive IGF2BP3 expression was related to poor distant metastasis-free survival (DMFS, p = .030) and Cox regression analysis identified IGF2BP3 as an independent risk factor for DMFS (hazard ratio, 1.876; 95% confidence interval, 1.128-3.159; p = .019). Positive IGF2BP3 expression was markedly related to breast cancer brain metastasis (p = .011) but not to lung and bone metastasis. Moreover, patients with IGF2BP3-positive brain metastasis had lower survival than patients with IGF2BP3-negative brain metastasis (p = .041). Gene expression profiling results indicated that high IGF2BP3 expression was associated with the PD-1 checkpoint pathway, HER2-HER3 signaling, and epithelial-mesenchymal transition.

CONCLUSIONS

IGF2BP3 may serve as a novel predictive biomarker and a potential therapeutic target for breast cancer brain metastasis, which warrants further investigation.

PLAIN LANGUAGE SUMMARY

As an m6 A reader, IGF2BP3 is dysregulated and implicated in various cancers but its role in breast cancer has not been fully clarified. In this study, we found that IGF2BP3 was upregulated in breast cancer and IGF2BP3 expression increased gradually during breast cancer progression. IGF2BP3 expression exerted no effect on the overall survival and breast cancer-specific survival of breast cancer patients; however, IGF2BP3-positive patients were more likely to develop distant metastasis than IGF2BP3-negative patients. In addition, IGF2BP3 was associated with brain-specific metastasis in breast cancer patients. These findings warrant further investigation because they provide a rationale for novel predictive or therapeutic approaches.