Eliminating the breast cancer surgery paradigm after neoadjuvant systemic therapy: current evidence and future challenges

Design, synthesis, and biological studies of nitric oxide-donating piperlongumine derivatives triggered by lysyl oxidase as anti-triple negative breast cancer agents

Nitric oxide (NO) is an important gas messenger molecule with a wide range of biological functions. High concentration of NO exerts promising antitumor effects and is regarded as one of the hot spots in cancer research, that have limitations in their direct application due to its gaseous state, short half-life (seconds) and high reactivity. Lysyl oxidase (LOX) is a copper-dependent amine oxidase that is responsible for the covalent bonding between collagen and elastin and promotes tumor cell invasion and metastasis. The overexpression of LOX in triple-negative breast cancer (TNBC) makes it an attractive target for TNBC therapy. Herein, novel NO donor prodrug molecules were designed and synthesized based on the naturally derived piperlongumine (PL) skeleton, which can be selectively activated by LOX to release high concentrations of NO and PL derivatives, both of them play a synergistic role in TNBC therapy. Among them, the compound TM-1 selectively released NO in highly invasive TNBC cells (MDA-MB-231), and TM-1 was also confirmed as a potential TNBC cell line inhibitor with an inhibitory concentration of 2.274 μM. Molecular docking results showed that TM-1 had a strong and selective binding affinity with LOX protein.

Clinical applications of next-generation sequencing-based ctDNA analyses in breast cancer: defining treatment targets and dynamic changes during disease progression

The advancements in the detection and characterization of circulating tumor DNA (ctDNA) have revolutionized precision medicine and are likely to transform standard clinical practice. The non-invasive nature of this approach allows for molecular profiling of the entire tumor entity, while also enabling real-time monitoring of the effectiveness of cancer therapies as well as the identification of resistance mechanisms to guide targeted therapy. Although the field of ctDNA studies offers a wide range of applications, including in early disease, in this review we mainly focus on the role of ctDNA in the dynamic molecular characterization of unresectable locally advanced and metastatic BC (mBC). Here, we provide clinical practice guidance for the rapidly evolving field of molecular profiling of mBC, outlining the current landscape of liquid biopsy applications and how to choose the right ctDNA assay. Additionally, we underline the importance of exploring the clinical relevance of novel molecular alterations that potentially represent therapeutic targets in mBC, along with mutations where targeted therapy is already approved. Finally, we present a potential roadmap for integrating ctDNA analysis into clinical practice.

Machine learning approaches in the prediction of positive axillary lymph nodes post neoadjuvant chemotherapy using MRI, CT, or ultrasound: A systematic review

Background and objective

Neoadjuvant chemotherapy is a standard treatment approach for locally advanced breast cancer. Conventional imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound, have been used for axillary lymph node evaluation which is crucial for treatment planning and prognostication. This systematic review aims to comprehensively examine the current research on applying machine learning algorithms for predicting positive axillary lymph nodes following neoadjuvant chemotherapy utilizing imaging modalities, including MRI, CT, and ultrasound.

Methods

A systematic search was conducted across databases, including PubMed, Scopus, and Web of Science, to identify relevant studies published up to December 2023. Articles employing machine learning algorithms to predict positive axillary lymph nodes using MRI, CT, or ultrasound data after neoadjuvant chemotherapy were included. The review follows the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, encompassing data extraction and quality assessment.

Results

Seven studies were included, comprising 1502 patients. Four studies used MRI, two used CT, and one applied ultrasound. Two studies developed deep-learning models, while five used classic machine-learning models mainly based on multiple regression. Across the studies, the models showed high predictive accuracy, with the best-performing models combining radiomics and clinical data.

Conclusion

This systematic review demonstrated the potential of utilizing advanced data analysis techniques, such as deep learning radiomics, in improving the prediction of positive axillary lymph nodes in breast cancer patients following neoadjuvant chemotherapy.

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.

New Strategies for Locally Advanced Breast Cancer: A Review of Inflammatory Breast Cancer and Nonresponders

This review explores the new strategies around the management of locally advanced breast cancer (LABC), particularly for nonresponsive tumors and/or initially unresectable tumors at diagnosis, inclusive of inflammatory breast cancer. Nonresponders to neoadjuvant systemic therapy present a unique clinical challenge. Emerging medical therapeutics as well as considerations for use of radiotherapy and/or surgery in this setting are discussed. Specifically, the use of neoadjuvant radiotherapy for LABC and lymphedema prevention with lymphatic reconstruction following axillary lymph node dissection are reviewed.

Outcomes of sentinel node biopsy according to MRI response in an association with the subtypes in cN1-3 breast cancer after neoadjuvant systemic therapy, multicenter cohort study

BACKGROUND

This study investigated the feasibility of sentinel lymph node biopsy (SLNB) after neoadjuvant systemic therapy (NAST) in patients with initially high nodal burden.

METHODS

In the multicenter retrospective cohort, 388 individuals with cN1-3 breast cancer who underwent NAST and had SLNB followed by completion axillary lymph node dissection were included. In an external validation cohort, 267 patients with HER2+ or triple-negative breast cancer (TNBC) meeting similar inclusion criteria were included. Primary outcome was the false-negative rates (FNRs) of SLNB according to the MRI response and subtypes. We defined complete MRI responders as patients who experienced disappearance of suspicious features in the breast and axilla after NAST.

RESULTS

In the multicenter retrospective cohort, 130 (33.5%) of 388 patients were of cN2-3, and 55 (14.2%) of 388 patients showed complete MRI responses. In hormone receptor-positive HER2- (n = 207), complete and non-complete responders had a high FNRs (31.3% [95% CI 8.6-54.0] and 20.9% [95% CI 14.1-27.6], respectively). However, in HER2+ or TNBC (n = 181), the FNR of complete MRI responders was 0% (95% CI 0-0), whereas that of non-complete responders was 33.3% (95% CI 20.8-45.9). When we validated our findings in the external cohort with HER2+ or TNBC (n = 267), of which 34.2% were cN2-3, the FNRs of complete were 7.1% (95% CI 0-16.7).

CONCLUSIONS

Our findings suggest that SLNB can be a reliable option for nodal status evaluation in selected patients who have responded well to NAST, especially in HER2+ and TNBC patients who show a complete MRI response.

Organoid forming potential as complementary parameter for accurate evaluation of breast cancer neoadjuvant therapeutic efficacy

BACKGROUND

13-15% of breast cancer/BC patients diagnosed as pathological complete response/pCR after neoadjuvant systemic therapy/NST suffer from recurrence. This study aims to estimate the rationality of organoid forming potential/OFP for more accurate evaluation of NST efficacy.

METHODS

OFPs of post-NST residual disease/RD were checked and compared with clinical approaches to estimate the recurrence risk. The phenotypes of organoids were classified via HE staining and ER, PR, HER2, Ki67 and CD133 immuno-labeling. The active growing organoids were subjected to drug sensitivity tests.

RESULTS

Of 62 post-NST BC specimens, 24 were classified as OFP-I with long-term active organoid growth, 19 as OFP-II with stable organoid growth within 3 weeks, and 19 as OFP-III without organoid formation. Residual tumors were overall correlated with OFP grades (P < 0.001), while 3 of the 18 patients (16.67%) pathologically diagnosed as tumor-free (ypT0N0M0) showed tumor derived-organoid formation. The disease-free survival/DFS of OFP-I cases was worse than other two groups (Log-rank P < 0.05). Organoids of OFP-I/-II groups well maintained the biological features of their parental tumors and were resistant to the drugs used in NST.

CONCLUSIONS

The OFP would be a complementary parameter to improve the evaluation accuracy of NST efficacy of breast cancers.

Locoregional staging of breast cancer: contrast-enhanced mammography versus breast magnetic resonance imaging

PURPOSE

Breast cancer diagnosis often involves assessing the locoregional spread of the disease through MRI, as multicentricity, multifocality and/or bilaterality are increasingly common. Contrast-enhanced mammography (CEM) is emerging as a potential alternative method. This study compares the performance of CEM and MRI in preoperative staging of women with confirmed breast carcinoma. Patients were also asked to fill in a satisfaction questionnaire to rate their comfort level with each investigation.

METHODS

From May 1st, 2021 to May 1st, 2022, we enrolled 70 women with confirmed breast carcinoma who were candidates for surgery. For pre-operative locoregional staging, all patients underwent CEM and MRI examination, which two radiologists evaluated blindly. We further investigated all suspicious locations for disease spread, identified by both CEM and MRI, with a second-look ultrasound (US) and eventual histological examination.

RESULTS

In our study cohort, MRI and CEM identified 114 and 102 areas of focal contrast enhancement, respectively. A true discrepancy between MRI and CEM occurred in 9 out of 70 patients examined. MRI reported 8 additional lesions that proved to be false positives on second-look US in 6 patients, while it identified 4 lesions that were not detected by CEM and were pathological (true positives) in 3 patients.

CONCLUSIONS

CEM showed results comparable to MRI in the staging of breast cancer in our study population, with a high rate of patient acceptability.

Non-surgical ablation for breast cancer: an emerging therapeutic option

Non-surgical ablation is emerging as an alternative local therapy option for patients with early-stage breast cancer and encompasses two main types of percutaneous therapeutic procedures: radiofrequency ablation and cryoablation. Both techniques involve obliteration of a spherical lesion and feasibility studies have shown that complete tumour ablation is achievable with good or excellent cosmetic results. Although few clinical studies have directly compared non-surgical ablation with conventional surgical resection, observational studies indicate that clinical outcomes are favourable with acceptable rates of local control and no detriment to long-term survival. There remain outstanding issues with these percutaneous ablative techniques that require resolution before they could be incorporated into routine clinical practice. Hence, a consensus meeting was convened to discuss the challenges of non-surgical ablation and clarify indications for its use alongside clinical management pathways. In this Policy Review we will address some of the broader biological aspects of non-surgical ablation, including immune-modulatory effects and potential novel applications for the future.

Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept

BACKGROUND

Breast cancer patients with residual disease after neoadjuvant systemic treatment (NAST) have a worse prognosis compared with those achieving a pathologic complete response (pCR). Earlier identification of these patients might allow timely, extended neoadjuvant treatment strategies. We explored the feasibility of a vacuum-assisted biopsy (VAB) after NAST to identify patients with residual disease (ypT+ or ypN+) prior to surgery.

METHODS

We used data from a multicenter trial, collected at 21 study sites (NCT02948764). The trial included women with cT1-3, cN0/+ breast cancer undergoing routine post-neoadjuvant imaging (ultrasound, MRI, mammography) and VAB prior to surgery. We compared the findings of VAB and routine imaging with the histopathologic evaluation of the surgical specimen.

RESULTS

Of 398 patients, 34 patients with missing ypN status and 127 patients with luminal tumors were excluded. Among the remaining 237 patients, tumor cells in the VAB indicated a surgical non-pCR in all patients (73/73, positive predictive value [PPV] 100%), whereas PPV of routine imaging after NAST was 56.0% (75/134). Sensitivity of the VAB was 72.3% (73/101), and 74.3% for sensitivity of imaging (75/101).

CONCLUSION

Residual cancer found in a VAB specimen after NAST always corresponds to non-pCR. Residual cancer assumed on routine imaging after NAST corresponds to actual residual cancer in about half of patients. Response assessment by VAB is not safe for the exclusion of residual cancer. Response assessment by biopsies after NAST may allow studying the new concept of extended neoadjuvant treatment for patients with residual disease in future trials.

Omission of Breast Surgery in Predicted Pathologic Complete Response after Neoadjuvant Systemic Therapy: A Multicenter, Single-Arm, Non-inferiority Trial

PURPOSE

Advances in chemotherapeutic and targeted agents have increased pathologic complete response (pCR) rates after neoadjuvant systemic therapy (NST). Vacuum-assisted biopsy (VAB) has been suggested to accurately evaluate pCR. This study aims to confirm the non-inferiority of the 5-year disease-free survival of patients who omitted breast surgery when predicted to have a pCR based on breast magnetic resonance imaging (MRI) and VAB after NST, compared with patients with a pCR who had undergone breast surgery in previous studies.

METHODS

The Omission of breast surgery for PredicTed pCR patients wIth MRI and vacuum-assisted bIopsy in breaST cancer after neoadjuvant systemic therapy (OPTIMIST) trial is a prospective, multicenter, single-arm, non-inferiority study enrolling in 17 tertiary care hospitals in the Republic of Korea. Eligible patients must have a clip marker placed in the tumor and meet the MRI criteria suggesting complete clinical response (post-NST MRI size ≤ 1 cm and lesion-to-background signal enhancement ratio ≤ 1.6) after NST. Patients will undergo VAB, and breast surgery will be omitted for those with no residual tumor. Axillary surgery can also be omitted if the patient was clinically node-negative before and after NST and met the stringent criteria of MRI size ≤ 0.5 cm. Survival and efficacy outcomes are evaluated over five years.

DISCUSSION

This study seeks to establish evidence for the safe omission of breast surgery in exceptional responders to NST while minimizing patient burden. The trial will address concerns about potential undertreatment due to false-negative results and recurrence as well as improved patient-reported quality of life issues from the omission of surgery. Successful completion of this trial may reshape clinical practice for certain breast cancer subtypes and lead to a safe and less invasive approach for selected patients.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05505357. Registered on August 17, 2022. Clinical Research Information Service Identifier: KCT0007638. Registered on July 25, 2022.

Axillary lymph node dissection in triple-negative or HER2-positive breast cancer patients with clinical N2 achieving pathological complete response after neoadjuvant therapy: Is it necessary?

AIM

This study aims to identify suitable candidates for axillary sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) among clinical N2 (cN2) triple-negative (TN) or HER2 positive (HER2+）breast cancer patients following neoadjuvant therapy（NAT）.

BACKGROUND

Despite the substantial axillary burden in cN2 breast cancer patients, high pathological response rates can be achieved with NAT in TN or HER2+ subtypes, thus enabling potential downstaging of axillary surgery.

METHODS

A retrospective analysis was conducted on data from the CSBrS-012 study, screening 709 patients with initial cN2, either HER2+ or TN subtype, from January 1, 2010 to December 31, 2020. The correlation between axillary pathologic complete response (pCR) (yPN0) and breast pCR was examined.

RESULTS

Among the 177 cN2 patients who achieved breast pCR through NAT, 138 (78.0 %) also achieved axillary pCR. However, in the 532 initial clinical N2 patients who did not achieve breast pCR, residual axillary lymph node metastasis persisted in 77.4 % (412/532) of cases. The relative risk of residual axillary lymph node metastasis in patients who did not achieve breast pCR was 12.4 (8.1-19.1), compared to those who did achieve breast pCR, P < 0.001.

CONCLUSION

For cN2 TN or HER2+ breast cancer patients who achieve breast pCR following NAT, consideration could be given to downstaging and performing an axillary SLNB or TAD.

Predicting response to neoadjuvant chemotherapy with liquid biopsies and multiparametric MRI in patients with breast cancer

Accurate prediction of response to neoadjuvant chemotherapy (NAC) can help tailor treatment to individual patients' needs. Little is known about the combination of liquid biopsies and computer extracted features from multiparametric magnetic resonance imaging (MRI) for the prediction of NAC response in breast cancer. Here, we report on a prospective study with the aim to explore the predictive potential of this combination in adjunct to standard clinical and pathological information before, during and after NAC. The study was performed in four Dutch hospitals. Patients without metastases treated with NAC underwent 3 T multiparametric MRI scans before, during and after NAC. Liquid biopsies were obtained before every chemotherapy cycle and before surgery. Prediction models were developed using penalized linear regression to forecast residual cancer burden after NAC and evaluated for pathologic complete response (pCR) using leave-one-out-cross-validation (LOOCV). Sixty-one patients were included. Twenty-three patients (38%) achieved pCR. Most prediction models yielded the highest estimated LOOCV area under the curve (AUC) at the post-treatment timepoint. A clinical-only model including tumor grade, nodal status and receptor subtype yielded an estimated LOOCV AUC for pCR of 0.76, which increased to 0.82 by incorporating post-treatment radiological MRI assessment (i.e., the "clinical-radiological" model). The estimated LOOCV AUC was 0.84 after incorporation of computer-extracted MRI features, and 0.85 when liquid biopsy information was added instead of the radiological MRI assessment. Adding liquid biopsy information to the clinical-radiological resulted in an estimated LOOCV AUC of 0.86. In conclusion, inclusion of liquid biopsy-derived markers in clinical-radiological prediction models may have potential to improve prediction of pCR after NAC in breast cancer.

A prospective study on tumour response assessment methods after neoadjuvant endocrine therapy in early oestrogen receptor-positive breast cancer

BACKGROUND

Neoadjuvant endocrine therapy (NET) in oestrogen receptor-positive (ER+) /HER2-negative (HER2-) breast cancer allows real-time evaluation of drug efficacy as well as investigation of the biological and molecular changes that occur after estrogenic deprivation. Clinical and pathological evaluation after NET may be used to obtain prognostic and predictive information of tumour response to decide adjuvant treatment. In this setting, clinical scales developed to evaluate response after neoadjuvant chemotherapy are not useful and there are not validated biomarkers to assess response to NET beyond Ki67 levels and preoperative endocrine prognostic index score (mPEPI).

METHODS

In this prospective study, we extensively analysed radiological (by ultrasound scan (USS) and magnetic resonance imaging (MRI)) and pathological tumour response of 104 postmenopausal patients with ER+ /HER2- resectable breast cancer, treated with NET for a mean of 7 months prior to surgery. We defined a new score, tumour cellularity size (TCS), calculated as the product of the residual tumour cellularity in the surgical specimen and the tumour pathological size.

RESULTS

Our results show that radiological evaluation of response to NET by both USS and MRI underestimates pathological tumour size (path-TS). Tumour size [mean (range); mm] was: path-TS 20 (0-80); radiological-TS by USS 9 (0-31); by MRI: 12 (0-60). Nevertheless, they support the use of MRI over USS to clinically assess radiological tumour response (rad-TR) due to the statistically significant association of rad-TR by MRI, but not USS, with Ki67 decrease (p = 0.002 and p = 0.3, respectively) and mPEPI score (p = 0.002 and p = 0.6, respectively). In addition, we propose that TCS could become a new tool to standardize response assessment to NET given its simplicity, reproducibility and its good correlation with existing biomarkers (such as ΔKi67, p = 0.001) and potential added value.

CONCLUSION

Our findings shed light on the dynamics of tumour response to NET, challenge the paradigm of the ability of NET to decrease surgical volume and point to the utility of the TCS to quantify the scattered tumour response usually produced by endocrine therapy. In the future, these results should be validated in independent cohorts with associated survival data.

Artificial intelligence in breast ultrasound: application in clinical practice

Ultrasound (US) is a widely accessible and extensively used tool for breast imaging. It is commonly used as an additional screening tool, especially for women with dense breast tissue. Advances in artificial intelligence (AI) have led to the development of various AI systems that assist radiologists in identifying and diagnosing breast lesions using US. This article provides an overview of the background and supporting evidence for the use of AI in hand held breast US. It discusses the impact of AI on clinical workflow, covering breast cancer detection, diagnosis, prediction of molecular subtypes, evaluation of axillary lymph node status, and response to neoadjuvant chemotherapy. Additionally, the article highlights the potential significance of AI in breast US for low and middle income countries.

Different approaches to target volume definition and boost delivery in surgery de-escalation clinical trial in breast cancer patients with pathological complete response

PURPOSE

We evaluate various approaches to target volume definition and boost delivery in patients with complete response to neoadjuvant systemic therapy (NST) who were treated by radiotherapy without a surgery.

MATERIALS AND METHODS

A pathological complete response (pCR) was diagnosed in 21 of 27 patients included in "surgery de-escalation" prospective observation study. Clips were placed in the primary tumor volume (PrTV) before NST and during the vacuum aspiration biopsy. Twenty patients with pCR underwent the whole breast irradiation and a boost to the PrTV. High-dose rate brachytherapy (HDRB) was the basic technique for boost delivery. Finally, we identified the value of fused images (computed tomography [CT] before NST with simulation CT), clips and their combination for an accurate boost delivery.

RESULTS

A complete overlap between PrTV on pre-treatment CT with the localization of the clips on simulation CT was mentioned in 10, partial mismatch in three patients. In 12 of these 13 women, HDRB was successfully used for the boost delivery. In five cases we mentioned a marked discrepancy between the PrTV on fused images and the topography of the clips. In other two women we did not find clips on simulation CT. The fused images in five of these seven patients showed anatomical landmarks (scar, fibrosis) used for identification of the gross tumor volume. In all 20 women with pCR (average follow-up of 16.6 months), there were no locoregional recurrences.

CONCLUSION

Combination of the clips with fusion of pre-NST and simulation CTs is important for an accurate boost delivery.

Association of systemic inflammatory markers and tertiary lymphoid structure with pathological complete response in gastric cancer patients receiving preoperative treatment: a retrospective cohort study

BACKGROUND

Assessment of systemic and local immune responses is crucial in determining the efficacy of cancer interventions. The identification of specific factors that correlate with pathological complete response (pCR) is essential for optimizing treatment decisions.

METHODS

In this retrospective study, a total of 521 patients diagnosed with gastric adenocarcinoma who underwent curative gastrectomy following preoperative treatment were reviewed. Of these patients, 463 did not achieve pCR (non-pCR) and 58 achieved pCR. Clinicopathological factors were evaluated to identify predictors for pCR using a logistic regression model. Additionally, a smaller cohort (n=76) was derived using propensity score matching to investigate local immune response, specifically the features of tertiary lymphoid structure (TLS) using H&E staining, immunohistochemistry, and multiplex immunofluorescence.

RESULTS

The multivariate regression analysis demonstrated a significant association between low systemic inflammatory status and pCR, as evidenced by reduced levels of the combined systemic immune-inflammation index (SII) and neutrophil-to-lymphocyte ratio (NLR) (SII+NLR) (odds ratio: 3.33, 95% CI: 1.79-6.17, P<0.001). In the smaller cohort analysis, distinct TLS characteristics were correlated with the presence of pCR. Specifically, a higher density of TLS and a lower proportion of PD1+ cells and CD8+ cells within TLS in the tumor bed were strongly associated with pCR.

CONCLUSION

Both systemic and local immune profile were associated with pCR. A low level of SII+NLR served as an independent predictor of pCR, while distinct TLS features were associated with the presence of pCR. Focusing on the immune profile was crucial for optimal management of gastric cancer patients receiving preoperative treatment.

Non-Response of Epstein-Barr Virus-Associated Breast Cancer after Primary Chemotherapy: Report of Two Cases

Based on epidemiological evidence and molecular findings, a possible association of Epstein-Barr virus (EBV) with the carcinogenesis of breast cancer has been described. However, the frequency of EBV in breast cancer and the role of EBV regarding tumor progression or therapeutic results is largely unexplored. Here, we report on two cases of advanced, lymph node-positive invasive breast cancer of no special type (NST), histologically showing no clinical or histological evidence of tumor regression as an equivalent of a lack of response to primary systemic therapy. Both tumors were considered to be EBV-associated due to their positivity in EBV-encoded RNA (EBER) in situ hybridization (ISH) and their immunoreactivity against EBV Epstein-Barr nuclear antigen 1 (EBNA1). We hypothesize that the unusual non-response to chemotherapy in these cases of breast cancer classified as triple-negative and HER2-positive may be linked to the EBV co-infection of tumor cells. Therefore, EBV tumor testing should be considered in patients with breast cancer presenting with resistance to chemotherapy. This hypothesis may provide a new aspect in the context of EBV-associated mechanisms of tumor progression.

Evaluation of quality of life in breast cancer patients who underwent breast-conserving surgery or mastectomy using real-world data

BACKGROUND

Due to advances in the fight against breast cancer, aesthetic aspects and the prevention of breast deformities are playing an important role in surgical procedures. Currently the main form of breast cancer surgery is breast-conserving surgery (BCS), and even if mastectomy (MAS) is required, oncoplastic surgery and reconstruction options can improve outcomes, including health-related quality of life (QoL) of cancer patients. The purpose of this study was to assess whether surgery options induce different outcomes in self-reported QoL in guide-line treated breast cancer patients of the Network Oncology (NO).

METHODS

This prospective Real-World-Data (RWD) study was conducted using data from the NO-clinical registry. QoL was assessed by evaluation of the European Organization of Research and Treatment Health-Related Quality of Life Core Questionnaire scale (EORTC QLQ-C30). Association factors between type of surgery options, without or with immediate breast reconstructions the EORTC QLQ-C30-scales at baseline after surgery, 6, 12, and 24 months later were analyzed with adjusted multivariate regression analysis, considering age, cancer stage, and treatment regimens, using software R.

RESULTS

A total of 623 primary breast cancer patients (all tumor stages, median age 58 (ICR: 50-68) diagnosed and guide-line treated between 2013 and 2021), 524 BCS and 99 MAS, 24 of whom received immediate breast reconstruction (MBR), were eligible for analyses. Compared with BCS patients, MBR patients self-reported considerably lower global health, physical and social functioning, and higher burden of pain and financial difficulties at baseline. In later follow-up surveys, functional scales increased and symptoms decreased in all patients, and the differences between MAS and BCS equalized. Longitudinal analyses after 24 months were obtained from 258 patients and revealed that compared to 224 BCS, the 34 MAS patients reported increased social functioning (p = 0.04).

CONCLUSIONS

At 24 months after MAS, breast cancer patients' QoL improved compared with BCS, although impairments in QoL were reported immediately after MAS. A growing expertise in surgical procedures as well as supportive care is critical to optimizing patients' well-being. These findings may be considered when counseling breast cancer patients pre- and post-surgery.

TRIAL REGISTRATION NUMBER

DRKS00013335 on 27/11/2017 retrospectively registered.

Prognosis of post-neoadjuvant therapy patients who underwent immediate breast reconstruction: a SEER-based, propensity-matched study

OBJECTIVE

The application of immediate breast reconstruction (IBR) for post-neoadjuvant therapy (NAT) patients was controversial. The aim of this study was to investigate the long-term survival outcomes of IBR for these patients.

METHODS

Data between January 2010 and November 2017 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (PSM) was performed to reduce the influence of confounding factors between the mastectomy alone group (MA) and the mastectomy with IBR group (IBR). The rates of 5 year breast cancer-specific survival (BCSS) were compared by Kaplan-Meier curves with log-rank test.

RESULTS

The IBR was associated with improved 5-year BCSS in the IBR group before PSM (88.5 vs. 79.1%, P < 0.001). The proportion of IBR increased from 21.5% in 2010 to 28.2% in 2017. After PSM, a total of 9,610 patients were enrolled for survival analysis (4,805 in each group). In the complete response (CR) group, the 5-year BCSS rates did not differ (93.4 vs. 95.6%, P = 0.16). In the non-CR group, the 5-year BCSS rate was higher in patients who received IBR (82.5% 79.4%, P = 0.034).

CONCLUSION

In general, the application of IBR among post-NAT patients has steadily increased from 2010 to 2017. In the CR group, survival outcomes of post-NAT patients who received IBR were similar to those who received mastectomy alone. In the non-CR group, IBR was associated with potential survival benefits. More studies are expected to validate our findings.

Efficacy comparisons of solvent-based paclitaxel, liposomal paclitaxel, nanoparticle albumin-bound paclitaxel, and docetaxel after neoadjuvant systemic treatment in breast cancer

PURPOSE

There are four kinds of taxanes: solvent-based paclitaxel (Sb-P), liposomal paclitaxel (Lps-P), nanoparticle albumin-bound paclitaxel (Nab-P), and docetaxel. This study aims to retrospectively evaluate the efficacy of different taxanes on neoadjuvant systemic treatment (NST) in breast cancer.

METHODS

Patients who were diagnosed with breast cancer and had received integral NST from August 2013 to April 2022 were enrolled. The efficacy was divided into total pathological complete response (total-pCR), breast pathological complete response (breast-pCR), and axillary pathological complete response (axillary-pCR) for in-depth analysis and discussion.

RESULTS

The choice of taxane was an independent risk factor for total-pCR and breast-pCR rates. The highest total-pCR and breast-pCR rates were found in the Nab-P group. The difference was not significant among all the taxanes in the axillary-pCR rate.

CONCLUSION

Nab-P significantly improved the total-pCR and breast-pCR rates. It should be the first choice among taxanes in NST for breast cancer.

Head-to-head comparison of contrast-enhanced mammography and contrast-enhanced MRI for assessing pathological complete response to neoadjuvant therapy in patients with breast cancer: a meta-analysis

OBJECTIVE

Breast cancer patients receiving neoadjuvant therapy (NAT) are in need of a more patient-friendly imaging modality such as contrast-enhanced mammography (CEM) for monitoring therapy response. The purpose of this study was to conduct a meta-analysis to compare the diagnostic performances of CEM and contrast-enhanced magnetic resonance imaging (CE-MRI) for assessing pathological complete response (pCR) in these patients.

METHODS

The PubMed, Embase, and Cochrane Library databases were searched through March 2023 to identify studies reporting a head-to-head comparison of CEM and CE-MRI in detecting pCR in breast cancer patients receiving NAT. Pooled diagnostic performance was calculated using a bivariate random-effects model, and an AUC was derived for each test from hierarchic summary ROC analysis.

RESULTS

Six studies with 328 patients were included. Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) were 93% (95% CI 84-97%), 68% (95% CI 60-76%), and 29.29 (95% CI 11.41-75.18) for CEM versus 84% (95% CI 62-95%), 80% (95% CI 71-87%), and 21.39 (95% CI 5.94-77.13) for CE-MRI. The AUC was 0.85 (95% CI 0.82-0.88) for CEM and 0.85 (95% CI 0.82-0.88) for CE-MRI.

CONCLUSION

This meta-analysis of head-to-head comparison studies showed that CEM provides an equivalent diagnostic accuracy to CE-MRI in identification of pCR in breast cancer patients receiving NAT. The results support the increasing use of CEM in this setting and would encourage future studies to validate CEM as a suitable replacement for MRI.

Ten-Year Oncologic Outcomes in T1-3N1 Breast Cancer After Targeted Axillary Sampling: A Retrospective Study

BACKGROUND

Targeted axillary sampling (TAS) is a new surgical concept for the assessment of axillary lymph node status in breast cancer that is hypothesized to be more effective at minimizing postoperative morbidities than axillary lymph node dissection (ALND), provided the metastatic axillary lymph node can be accurately detected without missing data; however, the oncologic outcomes over long-term follow-up have not been sufficiently investigated. This was a retrospective analysis to evaluate the 10-year oncologic outcomes in T1-3N1 breast cancer after TAS.

METHODS

Between 2008 and 2013, 230 female patients with cT1-3N1 breast cancer underwent breast and axillary surgery (ALND, n = 171; TAS, n = 59) at our institute. After TAS was applied, additional axillary radiotherapy was performed. Various postoperative complications, including postoperative seroma, lymphedema, and 10-year oncological outcomes, were evaluated and compared between the ALND and TAS groups.

RESULTS

Although overall survival during the 10-year follow-up period was better in the TAS group, there was no statistically significant difference in oncologic outcomes, including locoregional recurrence, distant metastasis, and overall survival (p = 0.395, 0.818, and 0.555, respectively). Furthermore, the incidence of lymphedema on the ipsilateral arm was significantly higher in the ALND group (p < 0.001).

CONCLUSIONS

The 10-year oncological outcomes of TAS were not inferior to those of conventional ALND in T1-3N1 breast cancers; however, the incidence of lymphedema was significantly higher in the ALND group.

Conventional specimen radiography in breast-conserving therapy: a useful tool for intraoperative margin assessment after neoadjuvant therapy?

PURPOSE

A previous study in our breast unit showed that the diagnostic accuracy of intraoperative specimen radiography and its potential to reduce second surgeries in a cohort of patients treated with neoadjuvant chemotherapy were low, which questions the routine use of Conventional specimen radiography (CSR) in this patient group. This is a follow-up study in a larger cohort to further evaluate these findings.

METHODS

This retrospective study included 376 cases receiving breast-conserving surgery (BCS) after neoadjuvant chemotherapy (NACT) of primary breast cancer. CSR was performed to assess potential margin infiltration and recommend an intraoperative re-excision of any radiologically positive margin. The histological workup of the specimen served as gold standard for the evaluation of the accuracy of CSR and the potential reduction of second surgeries by CSR-guided re-excisions.

RESULTS

362 patients with 2172 margins were assessed. The prevalence of positive margins was 102/2172 (4.7%). CSR had a sensitivity of 37.3%, a specificity of 85.6%, a positive predictive value (PPV) of 11.3%, and a negative predictive value (NPV) of 96.5%. The rate of secondary procedures was reduced from 75 to 37 with a number needed to treat (NNT) of CSR-guided intraoperative re-excisions of 10. In the subgroup of patients with clinical complete response (cCR), the prevalence of positive margins was 38/1002 (3.8%), PPV was 6.5% and the NNT was 34.

CONCLUSION

This study confirms our previous finding that the rate of secondary surgeries cannot be significantly reduced by CSR-guided intraoperative re-excisions in cases with cCR after NACT. The routine use CSR after NACT is questionable, and alternative tools of intraoperative margin assessment should be evaluated.

Optimal treatment strategy for hormone receptor-positive human epidermal growth factor receptor 2-negative breast cancer patients with 1-2 suspicious axillary lymph node metastases on breast magnetic resonance imaging: upfront surgery vs. neoadjuvant chemotherapy

Background

It is unclear whether upfront surgery or neoadjuvant chemotherapy is appropriate for first treatment in hormone receptor (HR)-positive human epidermal growth factor receptor 2 (HER2)-negative breast cancer patients with 1-2 suspicious axillary lymph node (ALN) metastases on preoperative breast magnetic resonance imaging (MRI).

Method

We identified 282 patients with HR+HER2- breast cancer and 1-2 suspicious ALN metastases on baseline breast MRI (147 received upfront surgery; 135 received neoadjuvant chemotherapy). We evaluated the predictive clinicopathological factors for pN2-3 in the adjuvant setting and axillary pathologic complete response (pCR) in the neoadjuvant setting.

Results

Lymphovascular invasion (LVI)-positive and clinical tumors >3 cm were significantly associated with pN2-3 in patients who received upfront surgery. The pN2-3 rate was 9.3% in patients with a clinical tumor ≤ 3 cm and LVI-negative versus 34.7% in the others (p < 0.001). The pN2-3 rate in patients with a clinical tumor ≤ 3 cm and LVI-negative and in the others were 9.3% versus 34.7% in all patients (p < 0.001), 10.7% versus 40.0% (p = 0.033) in patients aged < 50 years, and 8.5% versus 31.0% in patients aged ≥ 50 years (p < 0.001), respectively. In the neoadjuvant setting, patients with tumor-infiltrating lymphocytes (TILs) ≥ 20% had a higher axillary pCR than those with TILs < 20% (46.7% vs. 15.3%, p < 0.001). A similar significant finding was also observed in patients < 50 years.

Conclusions

Upfront surgery may be preferable for patients aged ≥ 50 years with a clinical tumor < 3 cm and LVI-negative, while neoadjuvant chemotherapy may be preferable for those aged < 50 years with TILs ≥ 20%.

18F-FDG PET-Derived Volume-Based Parameters to Predict Disease-Free Survival in Patients with Grade III Breast Cancer of Different Molecular Subtypes Candidates to Neoadjuvant Chemotherapy

We investigated whether baseline [¹⁸F] Fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography (PET)-derived semiquantitative parameters could predict disease-free survival (DFS) in patients with grade III breast cancer (BC) of different molecular subtypes candidate to neoadjuvant chemotherapy (NAC). For each ¹⁸F-FDG-PET/CT scan, the following parameters were calculated in the primary tumor (SUVmax, SUVmean, MTV, TLG) and whole-body (WB_SUVmax, WB_MTV, and WB_TLG). Receiver operating characteristic (ROC) analysis was used to determine the capability to predict DFS and find the optimal threshold for each parameter. Ninety-five grade III breast cancer patients with different molecular types were retrieved from the databases of the University Hospital of Padua and the University Hospital of Ferrara (luminal A: 5; luminal B: 34; luminal B-HER2: 22; HER2-enriched: 7; triple-negative: 27). In luminal B patients, WB_MTV (AUC: 0.75; best cut-off: WB_MTV > 195.33; SS: 55.56%, SP: 100%; p = 0.002) and WB_TLG (AUC: 0.73; best cut-off: WB_TLG > 1066.21; SS: 55.56%, SP: 100%; p = 0.05) were the best predictors of DFS. In luminal B-HER2 patients, WB_SUVmax was the only predictor of DFS (AUC: 0.857; best cut-off: WB_SUVmax > 13.12; SS: 100%; SP: 71.43%; p < 0.001). No parameter significantly affected the prediction of DFS in patients with grade III triple-negative BC. Volume-based parameters, extracted from baseline ¹⁸F-FDG PET, seem promising in predicting recurrence in patients with grade III luminal B and luminal B- HER2 breast cancer undergoing NAC.

Personalizing neoadjuvant immune-checkpoint inhibition in patients with melanoma

Neoadjuvant immune-checkpoint inhibition is a promising emerging treatment approach for patients with surgically resectable macroscopic stage III melanoma. The neoadjuvant setting provides an ideal platform for personalized therapy owing to the very homogeneous nature of the patient population and the opportunity for pathological response assessments within several weeks of starting treatment, thereby facilitating the efficient identification of novel biomarkers. A pathological response to immune-checkpoint inhibitors has been shown to be a strong surrogate marker of both recurrence-free survival and overall survival, enabling timely analyses of the efficacy of novel therapies in patients with early stage disease. Patients with a major pathological response (defined as the presence of ≤10% viable tumour cells) have a very low risk of recurrence, which offers an opportunity to adjust the extent of surgery and any subsequent adjuvant therapy and follow-up monitoring. Conversely, patients who have only a partial pathological response or who do not respond to neoadjuvant therapy still might benefit from therapy escalation and/or class switch during adjuvant therapy. In this Review, we outline the concept of a fully personalized neoadjuvant treatment approach exemplified by the current developments in neoadjuvant therapy for patients with resectable melanoma, which could provide a template for the development of similar approaches for patients with other immune-responsive cancers in the near future.

Initial Results of 68Ga-FAPI-46 PET/MRI to Assess Response to Neoadjuvant Chemotherapy in Breast Cancer

Improving imaging-based response after neoadjuvant chemotherapy (NAC) in breast cancer assessment could obviate histologic confirmation of pathologic complete response (pCR) and facilitate deescalation of chemotherapy or surgery. Fibroblast activation protein inhibitor (FAPI) PET/MRI is a promising novel molecular imaging agent for the tumor microenvironment with intense uptake in breast cancer. We assessed the diagnostic performance of follow-up breast 68Ga-FAPI-46 (68Ga-FAPI) PET/MRI in classifying the response status of local breast cancer and lymph node metastases after completion of NAC and validated this approach immunohistochemically. Methods: In women who completed NAC for invasive breast cancer, follow-up 68Ga-FAPI PET/MRI and corresponding fibroblast activation protein (FAP) immunostainings were retrospectively analyzed. Metrics of 68Ga-FAPI uptake and FAP immunoreactivity in women with or without pCR were compared using the Mann-Whitney U test. Diagnostic performance to detect remnant invasive cancer was calculated for tracer uptake metrics using receiver-operating-characteristic curves and for masked readers' visual assessment categories of PET/MRI and MRI alone. Results: Thirteen women (mean age ± SD, 47 ± 9 y) were evaluated. Seven of the 13 achieved pCR in the breast and 6 in the axilla. FAP immunoreactivity was significantly associated with response status. The 68Ga-FAPI PET/MRI mean breast tumor-to-background ratio was 0.9 (range, 0.6-1.2) for pCR and 2.1 (range, 1.4-3.1) for no pCR (P = 0.001). Integrated PET/MRI could classify breast response correctly in all 13 women based on readers' visual assessment or tumor-to-background ratio. Evaluation of MRI alone resulted in at least 2 false-positives. For lymph nodes, PET/MRI readers had at least 2 false-negative classifications, whereas MRI alone resulted in 2 false-negatives and 1 false-positive. Conclusion: To our knowledge, this was the first analysis of 68Ga-FAPI PET/MRI for response assessment after NAC for breast cancer. The diagnostic performance of PET/MRI in a small study sample trended toward a gain over MRI alone, clearly supporting future prospective studies.

Artificial intelligence to de-escalate loco-regional breast cancer treatment

In this review, we evaluate the potential and recent advancements in using artificial intelligence techniques to de-escalate loco-regional breast cancer therapy, with a special focus on surgical treatment after neoadjuvant systemic treatment (NAST). The increasing use and efficacy of NAST make the optimal loco-regional management of patients with pathologic complete response (pCR) a clinically relevant knowledge gap. It is hypothesized that patients with pCR do not benefit from therapeutic surgery because all tumor has already been eradicated by NAST. It is unclear, however, how residual cancer after NAST can be reliably excluded prior to surgery to identify patients eligible for omitting breast cancer surgery. Evidence from clinical trials evaluating the potential of imaging and minimally-invasive biopsies to exclude residual cancer suggests that there is a high risk of missing residual cancer. More recently, AI-based algorithms have shown promising results to reliably exclude residual cancer after NAST. This example illustrates the great potential of AI-based algorithms to further de-escalate and individualize loco-regional breast cancer treatment.

The underused potential of breast conserving therapy after neoadjuvant system treatment - Causes and solutions

Breast conserving therapy (BCT), consisting of breast conserving surgery and subsequent radiotherapy, is an equivalent option to mastectomy for women with early breast cancer. Although BCT after neoadjuvant systemic treatment (NAST) has been routinely recommend by international guidelines since many years, the rate of BCT worldwide varies largely and its potential is still underused. While the rate of BCT in western countries has increased over the past decades to currently about 70%, the rate of BCT is as low as 10% in other countries. In this review, we will evaluate the underused potential of breast conservation after NAST, identify causes, and discuss possible solutions. We identified clinical and non-clinical causes for the underuse of BCT after NAST including uncertainties within the community regarding oncologic outcomes, the correct tumor localization after NAST, the management of multifocal and multicentric tumors, margin assessment, disparities of socio-economic aspects on a patient and national level, and psychological biases affecting the shared decision-making process between patients and clinicians. Possible solutions to mitigate the underuse of BCT after NAST include interdisciplinary teams that keep the whole patient pathway in mind, optimized treatment counseling and shared decision-making, and targeted financial support to alleviate disparities.

Development and Assessment of a Novel Core Biopsy-Based Prediction Model for Pathological Complete Response to Neoadjuvant Chemotherapy in Women with Breast Cancer

Purpose: Pathological complete response (pCR), the goal of NAC, is considered a surrogate for favorable outcomes in breast cancer (BC) patients administrated neoadjuvant chemotherapy (NAC). This study aimed to develop and assess a novel nomogram model for predicting the probability of pCR based on the core biopsy. Methods: This was a retrospective study involving 920 BC patients administered NAC between January 2012 and December 2018. The patients were divided into a primary cohort (769 patients from January 2012 to December 2017) and a validation cohort (151 patients from January 2017 to December 2018). After converting continuous variables to categorical variables, variables entering the model were sequentially identified via univariate analysis, a multicollinearity test, and binary logistic regression analysis, and then, a nomogram model was developed. The performance of the model was assessed concerning its discrimination, accuracy, and clinical utility. Results: The optimal predictive threshold for estrogen receptor (ER), Ki67, and p53 were 22.5%, 32.5%, and 37.5%, respectively (all p < 0.001). Five variables were selected to develop the model: clinical T staging (cT), clinical nodal (cN) status, ER status, Ki67 status, and p53 status (all p ≤ 0.001). The nomogram showed good discrimination with the area under the curve (AUC) of 0.804 and 0.774 for the primary and validation cohorts, respectively, and good calibration. Decision curve analysis (DCA) showed that the model had practical clinical value. Conclusions: This study constructed a novel nomogram model based on cT, cN, ER status, Ki67 status, and p53 status, which could be applied to personalize the prediction of pCR in BC patients treated with NAC.

Diagnostic performance of image-guided vacuum-assisted breast biopsy after neoadjuvant therapy for breast cancer: prospective pilot study

BACKGROUND

Image-guided vacuum-assisted breast biopsy (VABB) of the tumour bed, performed after neoadjuvant therapy, is increasingly being used to assess residual cancer and to potentially identify to identify pathological complete response (pCR). In this study, the accuracy of preoperative VABB specimens was assessed and compared with surgical specimens in patients with triple-negative or human epidermal growth factor receptor 2 (HER2)-positive invasive ductal breast cancer after neoadjuvant therapy. As a secondary endpoint, the performance of contrast-enhanced MRI of the breast and PET-CT for response prediction was assessed.

METHODS

This single-institution prospective pilot study enrolled patients from April 2018 to April 2021 with a complete response on imaging (iCR) who subsequently underwent VABB before surgery. Those with a pCR at VABB were included in the primary analysis of the accuracy of VABB. The performance of imaging (MRI and PET-CT) was analysed for prediction of a pCR considering both patients with an iCR and those with residual disease at postneoadjuvant therapy imaging.

RESULTS

Twenty patients were included in the primary analysis. The median age was 44 (range 35-51) years. At surgery, 18 of 20 patients showed a complete response (accuracy 90 (95 per cent exact c.i. 68 to 99) per cent). Only two patients showed residual ductal intraepithelial neoplasia of grade 2 and 3 respectively. In the secondary analysis, accuracy was similar for MRI and PET-CT (77 versus 78 per cent; P = 0.76).

CONCLUSION

VABB in patients with an iCR might be a promising method to select patients for de-escalation of surgical treatment in triple-negative or HER2-positive breast cancer. The present results support such an approach and should inform the design of future trials on de-escalation of surgery.

Assessment and Response to Neoadjuvant Treatments in Breast Cancer: Current Practice, Response Monitoring, Future Approaches and Perspectives

Neoadjuvant treatments (NAT) for breast cancer (BC) consist in the administration of chemotherapy-more rarely endocrine therapy-before surgery. Firstly, it was introduced 50 years ago to downsize locally advanced (inoperable) BCs. NAT are now widespread and so effective to be used also at the early stage of the disease. NAT are heterogeneous in terms of therapeutic patterns, class of used drugs, dosage, and duration. The poly-chemotherapy regimen and administration schedule are established by a multi-disciplinary team, according to the stage of disease, the tumor subtype and the age, the physical status, and the drug sensitivity of BC patients. Consequently, an accurate monitoring of treatment response can provide significant clinical advantages, such as the treatment de-escalation in case of early recognition of complete response or, on the contrary, the switch to an alternative treatment path in case of early detection of resistance to the ongoing therapy. Future is going toward increasingly personalized therapies and the prediction of individual response to treatment is the key to practice customized care pathways, preserving oncological safety and effectiveness. To gain such goal, the development of an accurate monitoring system, reproducible and reliable alone or as part of more complex diagnostic algorithms, will be promising.

Pathologic Response of Associated Ductal Carcinoma In Situ to Neoadjuvant Systemic Therapy: A Systematic Review

Contrary to traditional assumptions, recent evidence suggests that neoadjuvant systemic therapy (NST) given for invasive breast cancer may eradicate co-existent ductal carcinoma in-situ (DCIS), which may facilitate de-escalation of breast resections. The aim of this systematic review was to assess the eradication rate of DCIS by NST given for invasive breast cancer. Searches were performed in MEDLINE using appropriate search terms. Six studies (N = 659) in which pathological data were available regarding the presence of DCIS prior to neoadjuvant chemotherapy (NACT) were identified. Only one study investigating the impact of neoadjuvant endocrine therapy (NET) met the search criteria. After pooled analysis, post-NACT pathology showed no residual DCIS in 40.5% of patients (267/659; 95% CI: 36.8-44.3). There was no significant difference in DCIS eradication rate between triple negative breast cancer (TNBC) and HER2-positive disease (45% vs. 46% respectively). NET achieved eradication of DCIS in 15% of patients (9/59). Importantly, residual widespread micro-calcifications after NST did not necessarily indicate residual disease. In view of the results of the pooled analysis, the presence of extensive DCIS prior to NST should not mandate mastectomy and de-escalation to breast conserving surgery (BCS) should be considered in patients identified by contrast enhanced magnetic resonance imaging (CE-MRI).

Integration of Clinical and CT-Based Radiomic Features for Pretreatment Prediction of Pathologic Complete Response to Neoadjuvant Systemic Therapy in Breast Cancer

The purpose of the present study was to examine the potential of a machine learning model with integrated clinical and CT-based radiomics features in predicting pathologic complete response (pCR) to neoadjuvant systemic therapy (NST) in breast cancer. Contrast-enhanced CT was performed in 329 patients with breast tumors (n = 331) before NST. Pyradiomics was used for feature extraction, and 107 features of seven classes were extracted. Feature selection was performed on the basis of the intraclass correlation coefficient (ICC), and six ICC thresholds (0.7−0.95) were examined to identify the feature set resulting in optimal model performance. Clinical factors, such as age, clinical stage, cancer cell type, and cell surface receptors, were used for prediction. We tried six machine learning algorithms, and clinical, radiomics, and clinical−radiomics models were trained for each algorithm. Radiomics and clinical−radiomics models with gray level co-occurrence matrix (GLCM) features only were also built for comparison. The linear support vector machine (SVM) regression model trained with radiomics features of ICC ≥0.85 in combination with clinical factors performed the best (AUC = 0.87). The performance of the clinical and radiomics linear SVM models showed statistically significant difference after correction for multiple comparisons (AUC = 0.69 vs. 0.78; p < 0.001). The AUC of the radiomics model trained with GLCM features was significantly lower than that of the radiomics model trained with all seven classes of radiomics features (AUC = 0.85 vs. 0.87; p = 0.011). Integration of clinical and CT-based radiomics features was helpful in the pretreatment prediction of pCR to NST in breast cancer.

Clearance of ctDNA in triple-negative and HER2-positive breast cancer patients during neoadjuvant treatment is correlated with pathologic complete response

BACKGROUND

Although the standard of care is to perform surgery of primary breast cancer (BC) after neoadjuvant chemotherapy (NAC), for certain patients achieving clinical complete response (cCR) and pathologic complete response (pCR), omission of surgical treatment may be an option. Levels of circulating tumor DNA (ctDNA) during and after therapy could identify patients achieving minimal residual disease. In this study, we evaluated whether ctDNA clearance during NAC could be a correlate to effective response in human epidermal growth factor receptor 2 positive (HER2+) and triple-negative (TN) BC patients.

METHODS

A prospective study was conducted to identify patient-specific PIK3CA and TP53 mutations in tissue using next-generation sequencing, which could then be used to track the presence/absence of mutations prior to, during, and following NAC using Sysmex SafeSEQ technology. All patients underwent a surgical excision after NAC, and pCR was assessed.

RESULTS

A total of 29 TN and HER2+ BC patients were examined and 20 that carried mutations in the PIK3CA and/or TP53 genes were recruited. Overall, 19 of these 20 patients harbored at least one tumor-specific mutation in their plasma at baseline. After NAC, 15 patients (75.0%) achieved pCR according to the histopathologic evaluation of the surgical specimen, and 15 patients (75.0%) had a cCR; 18 of 20 patients (90.0%) had concordant pCR and cCR. The status of 'no mutation detected' (NMD) following NAC in cCR patients correctly identified the pCR in 14 of 15 patients (93.33%), as well as correctly ruled out pCR in three patients, with an accuracy of 89.47%. During the 12-month follow-up after surgery, 40 plasma samples collected from 15 patients all showed no detectable ctDNA (NMD), and no patient recurred.

CONCLUSION

These findings prompt further research of the value of ctDNA for non-invasive prediction of clinical/pathological response, raising the possibility of sparing surgery following NAC in selected BC patients.

Staging Breast Cancer with MRI, the T. A Key Role in the Neoadjuvant Setting

Breast cancer (BC) is the most common cancer among women worldwide. Neoadjuvant chemotherapy (NACT) indications have expanded from inoperable locally advanced to early-stage breast cancer. Achieving a pathological complete response (pCR) has been proven to be an excellent prognostic marker leading to better disease-free survival (DFS) and overall survival (OS). Although diagnostic accuracy of MRI has been shown repeatedly to be superior to conventional methods in assessing the extent of breast disease there are still controversies regarding the indication of MRI in this setting. We intended to review the complex literature concerning the tumor size in staging, response and surgical planning in patients with early breast cancer receiving NACT, in order to clarify the role of MRI. Morphological and functional MRI techniques are making headway in the assessment of the tumor size in the staging, residual tumor assessment and prediction of response. Radiomics and radiogenomics MRI applications in the setting of the prediction of response to NACT in breast cancer are continuously increasing. Tailored therapy strategies allow considerations of treatment de-escalation in excellent responders and avoiding or at least postponing breast surgery in selected patients.

Machine learning in medicine: a practical introduction to techniques for data pre-processing, hyperparameter tuning, and model comparison

BACKGROUND

There is growing enthusiasm for the application of machine learning (ML) and artificial intelligence (AI) techniques to clinical research and practice. However, instructions on how to develop robust high-quality ML and AI in medicine are scarce. In this paper, we provide a practical example of techniques that facilitate the development of high-quality ML systems including data pre-processing, hyperparameter tuning, and model comparison using open-source software and data.

METHODS

We used open-source software and a publicly available dataset to train and validate multiple ML models to classify breast masses into benign or malignant using mammography image features and patient age. We compared algorithm predictions to the ground truth of histopathologic evaluation. We provide step-by-step instructions with accompanying code lines.

FINDINGS

Performance of the five algorithms at classifying breast masses as benign or malignant based on mammography image features and patient age was statistically equivalent (P > 0.05). Area under the receiver operating characteristics curve (AUROC) for the logistic regression with elastic net penalty was 0.89 (95% CI 0.85 - 0.94), for the Extreme Gradient Boosting Tree 0.88 (95% CI 0.83 - 0.93), for the Multivariate Adaptive Regression Spline algorithm 0.88 (95% CI 0.83 - 0.93), for the Support Vector Machine 0.89 (95% CI 0.84 - 0.93), and for the neural network 0.89 (95% CI 0.84 - 0.93).

INTERPRETATION

Our paper allows clinicians and medical researchers who are interested in using ML algorithms to understand and recreate the elements of a comprehensive ML analysis. Following our instructions may help to improve model generalizability and reproducibility in medical ML studies.

Three-Dimensional in Vitro Models: A Promising Tool To Scale-Up Breast Cancer Research

Common models used in breast cancer studies, including two-dimensional (2D) cultures and animal models, do not precisely model all aspects of breast tumors. These models do not well simulate the cell-cell and cell-stromal interactions required for normal tumor growth in the body and lake tumor like microenvironment. Three-dimensional (3D) cell culture models are novel approaches to studying breast cancer. They do not have the restrictions of these conventional models and are able to recapitulate the structural architecture, complexity, and specific function of breast tumors and provide similar in vivo responses to therapeutic regimens. These models can be a link between former traditional 2D culture and in vivo models and are necessary for further studies in cancer. This review attempts to summarize the most common 3D in vitro models used in breast cancer studies, including scaffold-free (spheroid and organoid), scaffold-based, and chip-based models, particularly focused on the basic and translational application of these 3D models in drug screening and the tumor microenvironment in breast cancer.

Systemic therapy for early-stage breast cancer: learning from the past to build the future

The treatment of breast cancer has improved dramatically over the past century, from a strictly surgical approach to a coordinated one, including local and systemic therapies. Systemic therapies for early-stage disease were initially tested against observation or placebo only in adjuvant trials. Subsequent clinical trials focusing on treatment ‘fine-tuning’ had a marked increase in cohort size, duration and costs, leading to a growing interest in the neoadjuvant setting in the past decade. Neoadjuvant trial designs have the advantages of enabling the direct evaluation of treatment effects on tumour diameter and offer unique translational research opportunities through the comparative analysis of tumour biology before, during and after treatment. Current technologies enabling the identification of better predictive biomarkers are shaping the new era of (neo)adjuvant trials. An urgent need exists to reinforce collaboration between the pharmaceutical industry and academia to share data and thus establish large databases of biomarker data coupled with patient outcomes that are easily accessible to the scientific community. In this Review, we summarize the evolution of (neo)adjuvant trials from the pre-genomic to the post-genomic era and provide critical insights into how neoadjuvant studies are currently designed, discussing the need for better end points and treatment strategies that are more personalized, including in the post-neoadjuvant setting.

Systemic therapies for early-stage disease have been tested in clinical trials for decades. The authors of this Review provide an overview of the evolution of (neo)adjuvant trials from the pre-genomic to the post-genomic era, focusing on design, end points and biomarkers that, together, could enable the delivery of more personalized treatment.

Systemic therapy for patients with early-stage breast cancer has dramatically improved over the past eight decades, and the aims and designs of (neo)adjuvant clinical trials have consistently evolved.

The transition of clinical trials from the pre-genomic to the post-genomic era has been based on a deeper understanding of disease biology and a higher level of interest in the discovery of molecular markers associated with a response to treatment.

The currently adopted approach to the design of neoadjuvant trials requires a new wave of changes, with the implementation of validated end points with more robust predictive associations with survival outcomes and more personalized treatment strategies (escalation and/or de-escalation).

The evolution towards a more personalized treatment approach is leading to increasing interest in the post-neoadjuvant setting to investigate new drugs specifically in patients with high-risk disease.

Optimizing the efficiency of the search for novel biomarkers that can guide treatment tailoring requires the establishment of large, well-annotated databases of candidate biomarkers linked with clinical outcomes that are also easily accessible to the scientific community.

Early sharing of data from clinical trials should be based on joint efforts and reinforced collaboration between the pharmaceutical industry and academic entities.

Multiple-parameter MRI after neoadjuvant systemic therapy combining clinicopathologic features in evaluating axillary pathologic complete response in patients with clinically node-positive breast cancer

OBJECTIVE

This study aimed to evaluate axillary pathologic complete response (pCR) after neoadjuvant systemic therapy (NST) in clinically node-positive breast cancer (BC) patients based on post-NST multiple-parameter MRI and clinicopathological characteristics.

METHODS

In this retrospective study, females with clinically node-positive BC who received NST and followed by surgery between January 2017 and September 2021 were included. All axillary lymph nodes (ALNs) on MRI were matched with pathology by ALN markers or sizes. MRI morphological parameters, signal intensity curve (TIC) patterns and apparent diffusion coefficient (ADC) values of post-NST ALNs were measured. The clinicopathological characteristics was also collected and analyzed. Univariable and multivariable logistic regression analyses were performed to evaluate the independent predictors of axillary pCR.

RESULTS

Pathologically confirmed 137 non-pCR ALNs in 71 patients and 87 pCR ALNs in 87 patients were included in this study. Cortical thickness, fatty hilum, and TIC patterns of ALNs, hormone receptor, and human epidermal growth factor receptor 2 (HER2) status were significantly different between the two groups (all, p < 0.05). There was no significant difference for ADC values (p = 0.875). On multivariable analysis, TIC patterns (odds ratio [OR], 2.67, 95% confidence interval [CI]: 1.33, 5.34, p = 0.006), fatty hilum (OR, 2.88, 95% CI:1.39, 5.98, p = 0.004), hormone receptor (OR, 8.40, 95% CI: 2.48, 28.38, p = 0.001) and HER2 status (OR, 8.57, 95% CI: 3.85, 19.08, p < 0.001) were identified as independent predictors associated with axillary pCR. The area under the curve of the multivariate analysis using these predictors was 0.85 (95% CI: 0.79, 0.91).

CONCLUSION

Combining post-NST multiple-parameter MRI and clinicopathological characteristics allowed more accurate identification of BC patients who had received axillary pCR after NST.

ADVANCES IN KNOWLEDGE

A combined model incorporated multiple-parameter MRI and clinicopathologic features demonstrated good performance in evaluating axillary pCR preoperatively and non-invasively.

MRI to assess response after neoadjuvant chemotherapy in breast cancer subtypes: a systematic review and meta-analysis

This meta-analysis aimed to estimate and compare sensitivity, specificity, positive- (PPV) and negative predictive value (NPV) of magnetic resonance imaging (MRI) for predicting pathological complete remission (pCR) after neoadjuvant chemotherapy (NAC) in patients with early-stage breast cancer. We stratified for molecular subtype by immunohistochemistry (IHC) and explored the impact of other factors. Two researchers systematically searched PUBMED and EMBASE to select relevant studies and extract data. For meta-analysis of sensitivity and specificity, we used bivariate random-effects models. Twenty-six included studies contained 4497 patients. There was a significant impact of IHC subtype on post-NAC MRI accuracy (p = 0.0082) for pCR. The pooled sensitivity was 0.67 [95% CI 0.58-0.74] for the HR-/HER2-, 0.65 [95% CI 0.56-0.73] for the HR-/HER2+, 0.55 [95% CI 0.45-0.64] for the HR+/HER2- and 0.60 [95% CI 0.50-0.70] for the HR+/HER2+ subtype. The pooled specificity was 0.85 [95% CI 0.81-0.88] for the HR-/HER2-, 0.81 [95% CI 0.74-0.86] for the HR-/HER2+, 0.88[95% CI 0.84-0.91] for the HR+/HER2- and 0.74 [95% CI 0.63-0.83] for the HR+/HER2+ subtype. The PPV was highest in the HR-/HER2- subtype and lowest in the HR+/HER2- subtype. MRI field strength of 3.0 T was associated with a higher sensitivity compared to 1.5 T (p = 0.00063). The accuracy of MRI for predicting pCR depends on molecular subtype, which should be taken into account in clinical practice. Higher MRI field strength positively impacts accuracy. When intervention trials based on MRI response evaluation are designed, the impact of IHC subtype and field strength on MR accuracy should be considered.

Preoperative Breast Magnetic Resonance Imaging as a Predictor of Response to Neoadjuvant Chemotherapy

Introduction:

The ability to accurately predict pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer would improve patient selection for specific treatment strategies, would provide important information for patients to aid in the treatment selection process, and could potentially avoid the need for more extensive surgery. The diagnostic performance of magnetic resonance imaging (MRI) in predicting pCR has previously been studied, with mixed results. Magnetic resonance imaging performance may also be influenced by tumour and patient factors.

Methods:

Eighty-seven breast cancer patients who underwent NAC were studied. Pre-NAC and post-NAC MRI findings were compared with pathologic findings postsurgical excision. The impact of patient and tumour characteristics on MRI accuracy was evaluated.

Results:

The mean (SD) age of participants was 48.7 (10.3) years. The rate of pCR based on post-NAC MRI was 19.5% overall (19/87). The sensitivity, specificity, positive predictive value (PPV), negative predictive value, and accuracy in predicting pCR were 52.9%, 77.1%, 36.0%, 87.1%, and 72.4%, respectively. Positive predictive value was the highest in nonluminal versus Luminal A disease (45.0% vs 25.0%, P < .001), with higher rates of false positivity in nonluminal subtypes (P = .002). Tumour grade, T category, and histological subtype were all independent predictors of MRI accuracy regarding post-NAC tumour size.

Conclusion:

Magnetic resonance imaging alone is insufficient to accurately predict pCR in breast cancer patients post-NAC. Magnetic resonance imaging predictions of pCR are more accurate in nonluminal subtypes. Tumour grade, T category, and histological subtype should be considered when evaluating post-NAC tumour sizes.