Prognostic factors in breast cancer. College of American Pathologists Consensus Statement 1999

Artificial intelligence algorithm accurately assesses oestrogen receptor immunohistochemistry in metastatic breast cancer cytology specimens: A pilot study

OBJECTIVE

The Visiopharm artificial intelligence (AI) algorithm for oestrogen receptor (ER) immunohistochemistry (IHC) in whole slide images (WSIs) has been successfully validated in surgical pathology. This study aimed to assess its efficacy in cytology specimens.

METHODS

The study cohort comprised 105 consecutive cytology specimens with metastatic breast carcinoma. ER IHC WSIs were seamlessly integrated into the Visiopharm platform from the Image Management System (IMS) during our routine digital workflow, and an AI algorithm was employed for analysis. ER AI scores were compared with pathologists' manual consensus scores. Optimization steps were implemented and evaluated to reduce discordance.

RESULTS

The overall concordance between pathologists' scores and AI scores was excellent (99/105, 94.3%). Six cases exhibited discordant results, including two false-negative (FN) cases due to abundant histiocytes incorrectly counted as negatively stained tumour cells by AI, two FN cases owing to weak staining, and two false-positive (FP) cases where pigmented macrophages were erroneously counted as positively stained tumour cells by AI. The Pearson correlation coefficient of ER-positive percentages between pathologists' and AI scores was 0.8483. Optimization steps, such as lowering the cut-off threshold and additional training using higher input magnification, significantly improved accuracy.

CONCLUSIONS

The automated ER AI algorithm demonstrated excellent concordance with pathologists' assessments and accurately differentiated ER-positive from ER-negative metastatic breast carcinoma cytology cases. However, precision in identifying tumour cells in cytology specimens requires further enhancement.

Incidence and Prognostic Significance of Androgen Receptors (AR) in Indian Triple-Negative Breast Cancer (TNBC)

Molecular sub-characterization of triple-negative breast cancer (TNBC) has great therapeutic and possibly prognostic implications. The primary aim of this study was to investigate the incidence of luminal androgen receptor (LAR) subtype of TNBC and secondary aims were sub-categorization and clinico-pathologic correlation of LAR breast cancers. Retrospective study (January 2008 and 31st of December 2018) consisting of 157 TNBC patients. Androgen receptor (AR) expression was measured by immunohistochemical analysis. One percent cutoff was set as a positive expression. Sub-categorization was done on the basis of EGFR (> 15% of tumor cells) and Ki-67 expression (low- < 11%, intermediate- 11-20%, and high- > 21%). AR expression was correlated with various clinico-pathologic features and outcomes of the patients. The incidence of AR expression in TNBC was 24.8%. Considering different thresholds of > 5%, > 10%, and > 20% immunostaining, the incidence of AR positivity was 18.4, 15.2, and 11.5% respectively. The incidence of Ki-67 (p = 0.89) and EGFR (p = 0.643) expression did not differ significantly in AR-positive and -negative TNBC. Based on EGFR expression 19, 67 and 14% patients were categorized as low, intermediate, and high risk respectively. Low-risk (p ≤ 0.001) and low-grade (p = 0.014) tumors were more likely to have > 10% AR expression. Clinico-pathological profile, response to neoadjuvant chemotherapy, disease-free survival (p = 0.458), and overall survival (p = 0.806) did not significantly differ between AR expressing and negative TNBC. On multivariate analysis, only tumor staging was a significant predictor of survival (p = 0.012) and AR expression of > 10% revealed a trend towards improved survival (p = 0.07). When considering only AR-positive TNBC, AR expression of > 10% (p = 0.038), distant metastases (p = 0.003), and EGFR status (p = 0.024) were significantly associated with survival. AR expression does not seem to very strongly correlate with prognosis in TNBC and further studies could focus more on its predictive role in deciding anti-androgen therapy.

Implementation of HER2 Testing in Endometrial Cancer, a Summary of Real-World Initial Experience in a Large Tertiary Cancer Center

HER2-targeted therapies have transformed the management of advanced or recurrent serous endometrial cancer (EC), leading to an increased clinical demand for HER2 testing. Despite its adoption in select academic centers, the global extent of such tumor testing is unclear. In this study, we report on the initial two-year experience of HER2 testing at a major academic center with a reference gynecologic oncology service and biomarker reference laboratory. All patients who underwent HER2 testing based on physician discretion, reflex HER2 testing, and reference laboratory requests were included. From February 2021 to October 2023, HER2 testing was performed on 192 tumor tissue samples from 180 EC patients. Serous carcinoma constituted 52% of samples, reflecting diagnostic challenges and limited therapeutic options for advanced EC. HER2 positivity was found in 28% of all cases and 30% of p53-aberrant cases. An immunohistochemistry (IHC) score of 3+ was found in 15% of samples, while IHC 2+ was found in 45% (13% IHC 2+/ISH+ and 32% IHC 2+/ISH-). The newly identified 'HER2-low' category comprised 46% of the samples. Heterogeneity was noted in 42% of HER2-positive cases, with complex patterns in 3%. NGS and HER2 IHC-FISH showed a 24% discordance, attributed to intratumoral heterogeneity, tumor cellularity, a small number of amplified cells, and the HER2/CEP17 ratio near the cut-off. This study offers real-world insights into HER2 testing in EC, highlighting the challenges and underscoring the need for standardized guidelines in specimen handling, proficiency testing, and scoring criteria to enhance patient management and therapeutic decision-making.

Breast Cancer Stage and Size Detected with Film versus Digital Mammography in New South Wales, Australia: A Population-Based Study Using Routinely Collected Data

BACKGROUND

Digital mammography has replaced film mammography in breast-screening programs globally, including Australia. This led to an increase in the rate of detection, but whether there was increased detection of clinically important cancers is uncertain.

METHODS

In this population-wide retrospective cohort study in New South Wales, Australia spanning 2004 to 2016 and including 4,631,656 screens, there were 22,965 cancers in women screened with film (n = 11,040) or digital mammography (n = 11,925). We examined the change in tumor characteristics overall and how these rates changed over time, accounting for changes in background rates using an interrupted time-series. Comparisons were made with unscreened women (n = 26,326) during this time.

RESULTS

We found increased detection of in situ cancer (3.36 per 10,000 screens), localized invasive, and smaller-sized breast cancers attributable to the change in mammography technology, whereas screen-detected intermediate-sized and metastatic breast cancers decreased. Rates of early-stage and intermediate-sized interval cancers increased, and late-stage (-1.62 per 10,000 screens) and large interval cancers decreased. In unscreened women, there were small increases in the temporal trends of cancers across all stages.

CONCLUSIONS

At least some of the increased detection of smaller early-stage cancers may have translated into a reduction in larger and late-stage cancers, indicating beneficial detection of cancers that would have otherwise progressed. However, the increased detection of smaller early-stage and small cancers may also have increased over-diagnosis of lesions that would otherwise have not caused harm.

IMPACT

Robust evaluation of potential benefits and harms is needed after changes to screening programs. See related In the Spotlight, p. 638.

2D graphene-based advanced nanoarchitectonics for electrochemical biosensors: Applications in cancer biomarker detection

Low-cost, rapid, and easy-to-use biosensors for various cancer biomarkers are of utmost importance in detecting cancer biomarkers for early-stage metastasis control and efficient diagnosis. The molecular complexity of cancer biomarkers is overwhelming, thus, the repeatability and reproducibility of measurements by biosensors are critical factors. Electrochemical biosensors are attractive alternatives in cancer diagnosis due to their low cost, simple operation, and promising analytical figures of merit. Recently graphene-derived nanostructures have been used extensively for the fabrication of electrochemical biosensors because of their unique physicochemical properties, including the high electrical conductivity, adsorption capacity, low cost and ease of mass production, presence of oxygen-containing functional groups that facilitate the bioreceptor immobilization, increased flexibility and mechanical strength, low cellular toxicity. Indeed, these properties make them advantageous compared to other alternatives. However, some drawbacks must be overcome to extend their use, such as poor and uncontrollable deposition on the substrate due to the low dispersity of some graphene materials and irreproducibility of the results because of the differences in various batches of the produced graphene materials. This review has documented the most recently developed strategies for electrochemical sensor fabrication. It differs in the categorization method compared to published works to draw greater attention to the wide opportunities of graphene nanomaterials for biological applications. Limitations and future scopes are discussed to advance the integration of novel technologies such as artificial intelligence, the internet of medical things, and triboelectric nanogenerators to eventually increase efficacy and efficiency.

Deep Learning-Based Computer-Aided Diagnosis for Breast Lesion Classification on Ultrasound: A Prospective Multicenter Study of Radiologists Without Breast Ultrasound Expertise

BACKGROUND. Computer-aided diagnosis (CAD) systems for breast ultrasound interpretation have been primarily evaluated at tertiary and/or urban medical centers by radiologists with breast ultrasound expertise. OBJECTIVE. The purpose of this study was to evaluate the usefulness of deep learning-based CAD software on the diagnostic performance of radiologists without breast ultrasound expertise at secondary or rural hospitals in the differentiation of benign and malignant breast lesions measuring up to 2.0 cm on ultrasound. METHODS. This prospective study included patients scheduled to undergo biopsy or surgical resection at any of eight participating secondary or rural hospitals in China of a breast lesion classified as BI-RADS category 3-5 on prior breast ultrasound from November 2021 to September 2022. Patients underwent an additional investigational breast ultrasound, performed and interpreted by a radiologist without breast ultrasound expertise (hybrid body/breast radiologists, either who lacked breast imaging subspecialty training or for whom the number of breast ultrasounds performed annually accounted for less than 10% of all ultrasounds performed annually by the radiologist), who assigned a BI-RADS category. CAD results were used to upgrade reader-assigned BI-RADS category 3 lesions to category 4A and to downgrade reader-assigned BI-RADS category 4A lesions to category 3. Histologic results of biopsy or resection served as the reference standard. RESULTS. The study included 313 patients (mean age, 47.0 ± 14.0 years) with 313 breast lesions (102 malignant, 211 benign). Of BI-RADS category 3 lesions, 6.0% (6/100) were upgraded by CAD to category 4A, of which 16.7% (1/6) were malignant. Of category 4A lesions, 79.1% (87/110) were downgraded by CAD to category 3, of which 4.6% (4/87) were malignant. Diagnostic performance was significantly better after application of CAD, in comparison with before application of CAD, in terms of accuracy (86.6% vs 62.6%, p < .001), specificity (82.9% vs 46.0%, p < .001), and PPV (72.7% vs 46.5%, p < .001) but not significantly different in terms of sensitivity (94.1% vs 97.1%, p = .38) or NPV (96.7% vs 97.0%, p > .99). CONCLUSION. CAD significantly improved radiologists' diagnostic performance, showing particular potential to reduce the frequency of benign breast biopsies. CLINICAL IMPACT. The findings indicate the ability of CAD to improve patient care in settings with incomplete access to breast imaging expertise.

Current Laboratory Testing Practices for Assessment of ERBB2/HER2 in Endometrial Serous Carcinoma and Colorectal Carcinoma

CONTEXT.—

Therapy targeted at human epidermal growth factor receptor 2 (HER2; also known as ERBB2) was used initially for breast and gastroesophageal carcinoma and has more recently been adopted for endometrial serous carcinoma (ESC) and colorectal carcinoma (CRC). There is evidence that predictive biomarker testing algorithms for HER2 must be tumor type specific and that an algorithm validated for one tumor type cannot be applied to another.

OBJECTIVE.—

To describe current laboratory practices for HER2 assessment in ESC and CRC.

DESIGN.—

We surveyed laboratories participating in the 2021 College of American Pathologists (CAP) HER2 immunohistochemistry proficiency testing program.

RESULTS.—

The survey was distributed to 1548 laboratories and returned by 1195, of which 83.5% (998) were in the United States. For ESC, 24.0% (287) of laboratories reported performing in-house testing for HER2 by immunohistochemical staining and/or in situ hybridization; of these, 44.3% (127) performed it reflexively on all cases of ESC. The most common criterion for evaluating HER2 was the American Society of Clinical Oncology/CAP 2018 guideline for breast carcinoma (69.0%; 194 of 281), whereas only 16.0% (45) of laboratories used guidelines specific to ESC. For CRC, 20.2% (239 of 1185) of laboratories performed in-house HER2 testing, and 82.0% of these (196) did the test only at the clinician's request. A plurality (49.4%; 115 of 233) used gastroesophageal cancer guidelines when scoring CRC, 30.0% (70) used the CRC scoring system from the HERACLES trial, and 16.3% (38) used the American Society of Clinical Oncology/CAP 2018 guideline for breast carcinoma.

CONCLUSIONS.—

Laboratories vary in their approach to HER2 testing in ESC and CRC. Most laboratories did not report using tumor type-specific recommendations for HER2 interpretation. The lack of standardization could present a challenge to evidence-based practice when considering targeted therapy for these diseases.

Applications of Artificial Intelligence in Breast Pathology

CONTEXT.—

Increasing implementation of whole slide imaging together with digital workflow and advances in computing capacity enable the use of artificial intelligence (AI) in pathology, including breast pathology. Breast pathologists often face a significant workload, with diagnosis complexity, tedious repetitive tasks, and semiquantitative evaluation of biomarkers. Recent advances in developing AI algorithms have provided promising approaches to meet the demand in breast pathology.

OBJECTIVE.—

To provide an updated review of AI in breast pathology. We examined the success and challenges of current and potential AI applications in diagnosing and grading breast carcinomas and other pathologic changes, detecting lymph node metastasis, quantifying breast cancer biomarkers, predicting prognosis and therapy response, and predicting potential molecular changes.

DATA SOURCES.—

We obtained data and information by searching and reviewing literature on AI in breast pathology from PubMed and based our own experience.

CONCLUSIONS.—

With the increasing application in breast pathology, AI not only assists in pathology diagnosis to improve accuracy and reduce pathologists' workload, but also provides new information in predicting prognosis and therapy response.

Axillary lymph node status and invasive lobular breast cancer : Analysis of the Clinical Tumor Register of the AGO Austria

BACKGROUND

Invasive lobular carcinoma (ILC) represents the second most common type of invasive breast cancer (BC). Although ILC generally have good prognostic properties (positive estrogen receptor, ER, low tumor grade), they are generally diagnosed at a more advanced stage. The data on the axillary lymph node status in ILC compared to invasive ductal carcinoma (IDC) are considered controversial. Therefore, the aim of this study was to compare the pathological node stage (pN) between ILC and IDC in an Austria-wide register.

METHODS

Data of the Clinical Tumor Register (Klinisches TumorRegister, KTR) of the Austrian Association for Gynecological Oncology (AGO) were retrospectively analyzed. Patients with primary early BC, invasive lobular or ductal, diagnosed between January 2014 and December 2018, and primary surgery were included. A total of 2127 tumors were evaluated and compared in 2 groups, ILC n = 303, IDC n = 1824.

RESULTS

A total of 2095 patients were analyzed in the study. In the multivariate analysis, pN2 and pN3 were observed significantly more frequently in ILC compared with IDC (odds ratio, OR 1.93; 95% confidence interval, CI 1.19-3.14; p = 0.008 and OR 3.22; 95% CI: 1.47-7.03; p = 0.003; respectively). Other factors associated with ILC were tumor grades 2 and 3, positive ER, and pathological tumor stage (pT) 2 and pT3. In contrast, concomitant ductal carcinoma in situ, overexpression of the human epidermal growth factor receptor 2 (HER2), and a moderate and high proliferation rate (Ki67) were found less frequently in ILC.

CONCLUSION

The data show an increased risk of extensive axillary lymph node metastasis (pN2/3) in ILC.

Prognostic disparities in young patients based on breast cancer subtype: A population-based study from the SEER database

Triple-negative breast cancer (TNBC) is associated with younger age and worse long-term survival. However, the characteristics and prognosis of different subtypes of breast cancer (BC) in young (<40 years) patients have not yet been elucidated. The present population-based study explored the clinical and pathological characteristics of young TNBC patients and investigated their long-term survival. We enrolled patients from the Surveillance, Epidemiology, and End Results database younger than 40 years of age with primary BC. Cases were defined as patients with TNBC (hormone receptor [HR]-/human epidermal growth factor receptor 2 [HER2]-), and controls were patients with other subtypes of BC (HR-/HER2+, HR+/HER2-, and HR+/HER2+). Demographic, pathological, and radiotherapy, chemotherapy, and surgery data were extracted and the overall survival was the primary endpoint. We enrolled 14,234 young patients with BC in the present study, of whom 2798 (19.7%) had TNBC and 11,436 (80.3%) had another BC subtype. A higher proportion of TNBC patients than non-TNBC patients had a more advanced tumor-node-metastasis stage (II-IV 80.5% vs 73.1%, P < .001), and smaller proportions underwent radiotherapy (50.0% vs 53.3%, P = .002) and surgery (91.8% vs 92.9%, P < .001). TNBC was associated with significantly lower 5-year survival rates than other subtypes among patients with regional node positivity (0, 1-3, 4-9, ≥10: 54.2% vs 57.7%, 44.2% vs 55.9%, 31.0% vs 52.0%, and 27.7% vs 38.8%, P < .001) and those with different lymph node ratios (low, intermediate, high: 50.9% vs 56.0%, 34.6% vs 53.6%, and 24.8% vs 44.8%, P < .001). Our research is the first to investigate the relevant characteristics of young TNBC patients in comparison with those of young non-TNBC patients based on the surveillance, epidemiology, and end results database. We found that young TNBC patients have a higher pathological stage and worse long-term survival than young patients with other BC subtypes. These findings have implications in identifying young patients with TNBC for aggressive therapy and further investigations should be performed to explore new multimodal treatments for such patients.

Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis

Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.

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.

Evaluating breast ultrasound S-detect image analysis for small focal breast lesions

Background

S-Detect is a computer-assisted, artificial intelligence-based system of image analysis that has been integrated into the software of ultrasound (US) equipment and has the capacity to independently differentiate between benign and malignant focal breast lesions. Since the revision and upgrade in both the breast imaging-reporting and data system (BI-RADS) US lexicon and the S-Detect software in 2013, evidence that supports improved accuracy and specificity of radiologists' assessment of breast lesions has accumulated. However, such assessment using S-Detect technology to distinguish malignant from breast lesions with a diameter no greater than 2 cm requires further investigation.

Methods

The US images of focal breast lesions from 295 patients in our hospital from January 2019 to June 2022 were collected. The BI-RADS data were evaluated by the embedded program and as manually modified prior to the determination of a pathological diagnosis. The receiver operator characteristic (ROC) curves were constructed to compare the diagnostic accuracy between the assessments of the conventional US images, the S-Detect classification, and the combination of the two.

Results

There were 326 lesions identified in 295 patients, of which pathological confirmation demonstrated that 239 were benign and 87 were malignant. The sensitivity, specificity, and accuracy of the conventional imaging group were 75.86%, 93.31%, and 88.65%. The sensitivity, specificity, and accuracy of the S-Detect classification group were 87.36%, 88.28%, and 88.04%, respectively. The assessment of the amended combination of S-Detect with US image analysis (Co-Detect group) was improved with a sensitivity, specificity, and accuracy of 90.80%, 94.56%, and 93.56%, respectively. The diagnostic accuracy of the conventional US group, the S-Detect group, and the Co-Detect group using area under curves was 0.85, 0.88 and 0.93, respectively. The Co-Detect group had a better diagnostic efficiency compared with the conventional US group (Z = 3.882, p = 0.0001) and the S-Detect group (Z = 3.861, p = 0.0001). There was no significant difference in distinguishing benign from malignant small breast lesions when comparing conventional US and S-Detect techniques.

Conclusions

The addition of S-Detect technology to conventional US imaging provided a novel and feasible method to differentiate benign from malignant small breast nodules.

Lymph Node Metastases Detection Using Gd2O3@PCD as Novel Multifunctional Contrast Imaging Agent in Metabolic Magnetic Resonance Molecular Imaging

Axillary lymph node detection is crucial to staging and prognosis of the lymph node metastatic spread in breast cancer. Currently, lymphoscintigraphy and blue dye, as the conventional methods to localize sentinel lymph nodes (SLNs), are invasive and can only be performed during surgery. This study has had a novel hybrid gadolinium oxide nanoparticle coating with Cyclodextrin-based polyester as a high-relaxivity T₁ magnetic resonance molecular imaging (MRMI) contrast agent (CA). Twelve female BALB/c mice were randomly divided into three groups of four mice; each group was injected with 4T₁ cells to obtain metastasis lymph nodes and diagnosed by using the 3D T₁W (VIBE) MRI (Siemens 3T, Prisma). The synthesized Gd₂O₃@PCD nanoparticles with a suitable particle size range of 20-40 nm have had much higher longitudinal relaxivity (r ₁) for Gd₂O₃@PCD and Gd-DOTA (Dotarem) with the values of 3.98 mM^-1·s^-1 ± 0.003 and 2.71 mM^-1·s^-1 ± 0.005, respectively. Identical MR images in coronal views were subsequently obtained to create time-intensity curves of the right axillary lymph nodes and to measure the contrast ratio (CR). The peak CR and qualitative assessment of axillary lymph nodes at five-time points were evaluated. After subcutaneous injection, the contrast ratio of axillary lymph node and tumor in mice exhibited CR peak of Gd₂O₃@PCD and Dotarem with the values of 2.21 ± 0.06 and 0.40 ± 0.004 for lymph node and 2.54 ± 0.04 and 1.21 ± 0.007 for the tumor, respectively. Furthermore, the lumbar-aortic lymph node is weakly visible in the original coronal image. In conclusion, the use of Gd₂O₃@PCD nanoparticles as novel MRMI CAs enables high resolution for the detection of lymph node metastasis in mice with the potential capability for breast cancer diagnostic imaging.

Image Analysis in Digital Pathology Utilizing Machine Learning and Deep Neural Networks

Detection of regions of interest (ROIs) in whole slide images (WSIs) in a clinical setting is a highly subjective and a labor-intensive task. In this work, recent developments in machine learning and computer vision algorithms are presented to assess their possible usage and performance to enhance and accelerate clinical pathology procedures, such as ROI detection in WSIs. In this context, a state-of-the-art deep learning framework (Detectron2) was trained on two cases linked to the TUPAC16 dataset for object detection and on the JPATHOL dataset for instance segmentation. The predictions were evaluated against competing models and further possible improvements are discussed.

Multimodal Prediction of Five-Year Breast Cancer Recurrence in Women Who Receive Neoadjuvant Chemotherapy

In current clinical practice, it is difficult to predict whether a patient receiving neoadjuvant chemotherapy (NAC) for breast cancer is likely to encounter recurrence after treatment and have the cancer recur locally in the breast or in other areas of the body. We explore the use of clinical history, immunohistochemical markers, and multiparametric magnetic resonance imaging (DCE, ADC, Dixon) to predict the risk of post-treatment recurrence within five years. We performed a retrospective study on a cohort of 1738 patients from Institut Curie and analyzed the data using classical machine learning, image processing, and deep learning. Our results demonstrate the ability to predict recurrence prior to NAC treatment initiation using each modality alone, and the possible improvement achieved by combining the modalities. When evaluated on holdout data, the multimodal model achieved an AUC of 0.75 (CI: 0.70, 0.80) and 0.57 specificity at 0.90 sensitivity. We then stratified the data based on known prognostic biomarkers. We found that our models can provide accurate recurrence predictions (AUC > 0.89) for specific groups of women under 50 years old with poor prognoses. A version of our method won second place at the BMMR2 Challenge, with a very small margin from being first, and was a standout from the other challenge entries.

CYP2S1 and CYP2W1 expression is associated with patient survival in breast cancer

The cytochrome P450 family of enzymes metabolise a wide range of compounds and play important roles in breast cancer pathogenesis due to their involvement in estrogen metabolism and the production of carcinogenic metabolites during this process. The orphan CYPs, CYP2S1, and CYP2W1 are reportedly upregulated in breast cancer. However, their expression and association with clinicopathological and survival parameters have not been previously assessed in a large cohort of breast cancers. Protein expression of CYP2S1 and CYP2W1 was assessed in early-stage invasive breast cancers (n = 1,426) using immunohistochemistry and correlated with various clinicopathological parameters and survival. mRNA expression of CYP2S1 and CYP2W1 was also assessed in the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) cohort. Low nuclear and cytoplasmic CYP2S1 was significantly associated with high-grade tumours (p ≤ 0.009), intermediate Nottingham prognostic index (NPI) group (p ≤ 0.025), high mitotic frequency (p ≤ 0.002), human epidermal growth factor receptor 2 (HER2)-negative disease (p ≤ 0.011), and ductal carcinoma (p ≤ 0.022). Cytoplasmic CYP2S1 was additionally associated with patients ≥50 years (p < 0.001), estrogen receptor (ER)-positive tumours (p = 0.011), and high nuclear pleomorphism (p = 0.003). Low cytoplasmic CYP2W1 was significantly associated with patients ≥50 years (p = 0.002), HER2-negative disease (p = 0.003), intermediate NPI (p = 0.013), and mitosis (p = 0.009). Low cytoplasmic CYP2S1 was significantly associated with adverse breast cancer specific survival (p = 0.034), which remained so in multivariate analysis (hazard ratio [HR]: 0.639; 95% confidence interval [CI]: 0.483-0.846; p = 0.002). Low nuclear CYP2W1 was significantly associated with adverse breast cancer specific survival (p = 0.012), with significance also maintained in multivariate analysis (HR: 0.677; 95% CI: 0.510-0.898; p = 0.007). No associations with survival were observed in the METABRIC cohort. CYP2S1 and CYP2W1 are associated with patient survival in breast cancer and may be important prognostic biomarkers.

Effectiveness of Quantitative Shear Wave Elastography for the Prediction of Axillary Lymph Node Metastasis

Objective

Invasive breast cancer can be metastasized through axillary lymph nodes (LNs). This study was to evaluate the effectiveness of quantitative shear wave elastography (SWE) to predict axillary LN metastasis, which also provides prognostic implication of SWE as a histopathologic element of invasive breast cancer.

Methods

72 prospectively enrolled patients received B-mode ultrasound (BUS) and SWE, and the elasticity index (EI) of SWE at the stiffest part of lymph nodes (LNs) was measured. EI of SWE was closely associated with pathologic results and the histopathologic elements. The receiver operating characteristics (ROC) curve was drawn to evaluate the optimal cut-off value for the assessment of disease severity.

Results

A significantly longer short-axis diameter and a larger maximal cortex were observed in malignant LNs than that in healthy LNs. The absence of the hilum was associated with metastatic LNs. The EI of SWE varied markedly between the benign and malignant LNs. The combination of E_{max and} BUS showed higher area under the curve (AUC) than BUS alone to predict metastatic LNs (0.7762 vs. 0.7230). EI of SWE in malignant lymph nodes those with extranodal extension are higher than those without extranodal extension.

Conclusions

Quantitative SWE provides a viable alternative for the assessment of axillary LN and shows great potential to predict pathological prognostic elements of metastatic axillary LNs in invasive breast cancer. Joint use of SWE and BUS allows examination of the predictive outcome of BUS for axillary lymph node metastasis in invasive breast cancer.

Digital Imaging Correlation of Immunohistochemistry and Fluorescence in Situ Hybridization in Breast Carcinoma Cases with HER2 Genetic Heterogeneity

Genetic Heterogeneity (GH) is a rare but important event in evaluation of HER2 amplification status. We investigated whether HER2 FISH Genetic Heterogeneity (GH) correlated with increased protein expression by immunohistochemistry (IHC) and/or morphologic features using image analyses. Retrospective search of HER2 FISH GH cases 2016-2020 was performed. Cases with both FISH and IHC slides available were considered eligible and were digitally imaged. Additional demographic, histological, and treatment information was compiled from pathology and medical records when available. Overall, 11/15 (73.3%) of the cases had HER2 FISH GH that matched to areas of HER2 over-expression or focally different morphology. Nine cases with areas of gene amplification overlapped with <10% of intense circumferential protein expression ("Mini 3+,"), and one case with focal micropapillary features. Clinical information was available on 6 (40%) patients, all were alive with no evidence of disease (mean follow up 30. 5 months; range 12-65 months). One patient with GH and a lymph node metastasis showed non-amplified population in the nodal tumor. GH when defined as discrete clusters of amplified cells following 2013 ASCO/CAP guidelines, -even when less than 10 % of the tumor cells-frequently has morphologic correlates such as focal intense protein overexpression or micropapillary morphology. Clinical significance of these focal gene amplification and protein over-expression needs to be further investigated.

Definition of High-Risk Early Hormone-Positive HER2−Negative Breast Cancer: A Consensus Review

Breast cancer is one of the major causes of cancer-related morbidity and mortality in women worldwide. During the past three decades, several improvements in the adjuvant treatment of hormone receptor-positive/HER2−negative breast cancer have been achieved with the introduction of optimized adjuvant chemotherapy and endocrine treatment. However, estimating the risk of relapse of breast cancer on an individual basis is still challenging. The IRIDE (hIGh Risk DEfinition in breast cancer) working group was established with the aim of reviewing evidence from the literature to synthesize the current relevant features that predict hormone-positive/HER2−negative early breast cancer relapse. A panel of experts in breast cancer was involved in identifying clinical, pathological, morphological, and genetic factors. A RAND consensus method was used to define the relevance of each risk factor. Among the 21 features included, 12 were considered relevant risk factors for relapse. For each of these, we provided a consensus statement and relevant comments on the supporting scientific evidence. This work may guide clinicians in the practical management of hormone-positive/HER2−negative early breast cancers.

Validity of 1% Hormonal Receptor Positivity Cutoff by the ASCO/College of American Pathologists Guidelines at the Georgia Cancer Center

PURPOSE

Treatment of breast cancer (BC) with borderline or low (1%-9%) estrogen and progesterone expression remains controversial, with recent data disputing ASCO/College of American Pathologists 2010 guidelines that lowered the threshold of receptor positivity from 10% to 1%. The objective of this retrospective study was to validate these guidelines at the Georgia Cancer Center with a high percentage of Black race.

METHODS

All female patients with invasive BC diagnosed between 2005 and 2010 at the Georgia Cancer Center were chart reviewed up to an 11-year follow-up with data cutoff at 2016. We used Cox regression to explore survival among three hormonal status (HS) groups (< 1%, 1%-9%, and ≥ 10%) adjusting for all known BC clinicopathologic variables. Fisher's exact test was used to evaluate response to endocrine therapy (ET).

RESULTS

Among 431 patients with mean age 59 years, 24.75% had HS < 1%, 17.5% HS 1%-9%, and 57.75% HS ≥ 10%. Race was 43.75% Black and 54% White. Disease stages were early (I-IIIA) in 84.4% and advanced (IIIB-IV) in 15.56%. Mortality in HS < 1% was significantly higher than that in HS ≥ 10% (hazard ratio [HR]: 1.8; 95% CI, 1.07 to 3.02), whereas no significant mortality difference between HS 1%-9% and HS ≥ 10% (HR: 1.05; 95% CI, 0.48 to 2.30) was observed. ET was protective, and treated patients had higher predicted survival than untreated patients in the 1%-9% group (HR: 0.10; 95% CI, 0.01 to 0.85). There was no significant mortality difference between ET-treated HS 1%-9% and ≥ 10% groups.

CONCLUSION

One percent cutoff predicted superior survival on treatment with ET compared with the other groups, and HS as low as 1%-9% was equiprognostic to HS ≥ 10%. Whether other factors such as lymphovascular invasion, grade, and other parameters change the behavior of the 1%-9% HS group remains to be explored.

Immunomagnetic microscopy of tumor tissues using quantum sensors in diamond

Histological imaging is essential for the biomedical research and clinical diagnosis of human cancer. Although optical microscopy provides a standard method, it is a persistent goal to develop new imaging methods for more precise histological examination. Here, we use nitrogen-vacancy centers in diamond as quantum sensors and demonstrate micrometer-resolution immunomagnetic microscopy (IMM) for human tumor tissues. We immunomagnetically labeled cancer biomarkers in tumor tissues with magnetic nanoparticles and imaged them in a 400-nm resolution diamond-based magnetic microscope. There is barely magnetic background in tissues, and the IMM can resist the impact of a light background. The distribution of biomarkers in the high-contrast magnetic images was reconstructed as that of the magnetic moment of magnetic nanoparticles by employing deep-learning algorithms. In the reconstructed magnetic images, the expression intensity of the biomarkers was quantified with the absolute magnetic signal. The IMM has excellent signal stability, and the magnetic signal in our samples had not changed after more than 1.5 y under ambient conditions. Furthermore, we realized multimodal imaging of tumor tissues by combining IMM with hematoxylin-eosin staining, immunohistochemistry, or immunofluorescence microscopy in the same tissue section. Overall, our study provides a different histological method for both molecular mechanism research and accurate diagnosis of human cancer.

Integrating and validating automated digital imaging analysis of estrogen receptor immunohistochemistry in a fully digital workflow for clinical use

Background

Design

Results

Conclusions

Evaluation of Angiogenesis by Using CD105 and CD34 in Sudanese Breast Cancer Patients

&lt;b&gt;Background and Objective:&lt;/b&gt; Angiogenesis is a mechanism by which new blood vessels are developed in healing and tumour tissues, where it is necessary for regeneration growth, tumour cells survival and metastasis. This study aimed to assess the angiogenesis mechanism among Sudanese females with breast cancer using anti-CD34 and anti-CD105 markers. &lt;b&gt;Materials and Methods:&lt;/b&gt; Three hundred female representative Formalin-Fixed Paraffin-Embedded (FFPE) breast tissue blocks were included in this study. Of the 300 representative tissue blocks, 200 were breast cancer patient's tissues (confirmed cases) and 100 were normal breast tissues (controls). Their ages mean±SD, 47.3±12.9 years. &lt;b&gt;Results:&lt;/b&gt; The results showed the MVD of CD34 significantly increased in malignant lesions as compared to normal breast tissues. The mean of MVD CD34 and MVD CD105 showed statistical differences among different histologic types of breast cancer. Also, a strong positive correlation was detected between the manual and automated MVD counting methods. Also, the current study revealed no significant differences were observed in mean MVD counting for both markers and menopausal status or the age groups of the study population. &lt;b&gt;Conclusion:&lt;/b&gt; The MVD is a good tool for assessing prognostic markers. The CD105 marker has a high specificity to the new evolving tumour vessels and is a useful predictor for angiogenesis and breast cancer metastasis.

A meta-analysis of the diagnostic performance of machine learning-based MRI in the prediction of axillary lymph node metastasis in breast cancer patients

Background

Despite that machine learning (ML)-based MRI has been evaluated for diagnosis of axillary lymph node metastasis (ALNM) in breast cancer patients, diagnostic values they showed have been variable. In this study, we aimed to assess the use of ML to classify ALNM on MRI and to identify potential covariates that might influence the diagnostic performance of ML.

Methods

A systematic research of PubMed, Embase, Web of Science, and the Cochrane Library was conducted until 27 December 2020 to collect the included articles. Subgroup analysis was also performed.

Findings

Fourteen studies assessing a total of 2247 breast cancer patients were included in the analysis. The overall AUC for ML in the validation set was 0.80 (95% confidence interval [CI] 0.76–0.83) with a negative predictive value of 0.83. The pooled sensitivity and specificity were 0.79 (95% CI 0.74–0.84) and 0.77 (95% CI 0.73–0.81), respectively. In the subgroup analysis of the validation set, T1-weighted contrast-enhanced (T1CE) imaging with ML yielded a higher sensitivity (0.80 vs. 0.67 vs. 0.76) than the T2-weighted fat-suppressed (T2-FS) imaging and diffusion-weighted imaging (DWI). Support vector machines (SVMs) had a higher specificity than linear regression (LR) and linear discriminant analysis (LDA) (0.79 vs. 0.78 vs. 0.75), whereas LDA showed a higher sensitivity than LR and SVM (0.83 vs. 0.70 vs. 0.77).

Interpretation

MRI sequences and algorithms were the main factors that affect the diagnostic performance of ML. Although its results were encouraging with the pooled sensitivity of around 0.80, it meant that 1 in 5 women that would go with undetected metastases, which may have a detrimental effect on the overall survival for 20% of patients with positive SLN status. Despite that a high NPV of 0.83 meant that ML could potentially benefit those with negative SLN, it might also translate to 1 in 5 tests being false negative. We would like to suggest that ML may not be yet usable in clinical routine especially when patient survival is used as a primary measurement of its outcome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13244-021-01034-1.

St Gallen 2019 guidelines understage the axilla in lobular breast cancer: a population-based study

BACKGROUND

The St Gallen 2019 guidelines for primary therapy of early breast cancer recommend omission of completion axillary lymph node dissection (cALND), regardless of histological type, in patients with one or two sentinel lymph node (SLN) metastases. Concurrently, adjuvant chemotherapy is endorsed for luminal A-like disease with four or more axillary lymph node (ALN) metastases. The aim of this study was to estimate the proportion of patients with invasive lobular cancer (ILC) versus invasive ductal cancer of no special type (NST) with one or two SLN metastases for whom cALND would have led to a recommendation for adjuvant chemotherapy.

METHODS

Patients with ILC and NST who had surgery between 2014 and 2017 were identified in the National Breast Cancer Register of Sweden. After exclusion of patients with incongruent or missing data, those who fulfilled the St Gallen 2019 criteria for cALND omission were included in the population-based study cohort.

RESULTS

Some 1886 patients in total were included in the study, 329 with ILC and 1507 with NST. Patients with ILC had a higher metastatic nodal burden and were more likely to have a luminal A-like subtype than those with NST. The prevalence of at least four ALN metastases was higher in ILC (31.0 per cent) than NST (14.9 per cent), corresponding to an adjusted odds ratio of 2.26 (95 per cent c.i. 1.59 to 3.21). Luminal A-like breast cancers with four or more ALN metastases were over-represented in ILC compared with NST, 52 of 281 (18.5 per cent) versus 43 of 1299 (3.3 per cent) (P < 0.001).

CONCLUSION

Patients with ILC more often have luminal A-like breast cancer with at least four nodal metastases. Omission of cALND in patients with luminal A-like invasive lobular cancer and one or two SLN metastases warrants future attention as there is a risk of nodal understaging and undertreatment in one-fifth of patients.

Nomogram model combining macro and micro tumor-associated collagen signatures obtained from multiphoton images to predict the histologic grade in breast cancer

The purpose of this study is to develop and validate a new nomogram model combining macro and micro tumor-associated collagen signatures obtained from multiphoton images to differentiate tumor grade in patients with invasive breast cancer. A total of 543 patients were included in this study. We used computer-generated random numbers to assign 328 of these patients to the training cohort and 215 patients to the validation cohort. Macroscopic tumor-associated collagen signatures (TACS1-8) were obtained by multiphoton microscopy at the invasion front and inside of the breast primary tumor. TACS corresponding microscopic features (TCMF) including morphology and texture features were extracted from the segmented regions of interest using Matlab 2016b. Using ridge regression analysis, we obtained a TACS-score for each patient based on the combined TACS1-8, and the least absolute shrinkage and selection operator (LASSO) regression was applied to select the most robust TCMF features to build a TCMF-score. Univariate logistic regression analysis demonstrates that the TACS-score and TCMF-score are significantly associated with histologic grade (odds ratio, 2.994; 95% CI, 2.013-4.452; P < 0.001; 4.245, 2.876-6.264, P < 0.001 in the training cohort). The nomogram (collagen) model combining the TACS-score and TCMF-score could stratify patients into Grade1 and Grade2/3 groups with the AUC of 0.859 and 0.863 in the training and validation cohorts. The predictive performance can be further improved by combining the clinical factors, achieving the AUC of 0.874 in both data cohorts. The nomogram model combining the TACS-score and TCMF-score can be useful in differentiating breast tumor patients with Grade1 and Grade2/3.

Assessment of mitotic activity in breast cancer: revisited in the digital pathology era

The assessment of cell proliferation is a key morphological feature for diagnosing various pathological lesions and predicting their clinical behaviour. Visual assessment of mitotic figures in routine histological sections remains the gold-standard method to evaluate the proliferative activity and grading of cancer. Despite the apparent simplicity of such a well-established method, visual assessment of mitotic figures in breast cancer (BC) remains a challenging task with low concordance among pathologists which can lead to under or overestimation of tumour grade and hence affects management. Guideline recommendations for counting mitoses in BC have been published to standardise methodology and improve concordance; however, the results remain less satisfactory. Alternative approaches such as the use of the proliferation marker Ki67 have been recommended but these did not show better performance in terms of concordance or prognostic stratification. The advent of whole slide image technology has brought the issue of mitotic counting in BC into the light again with more challenges to develop objective criteria for identifying and scoring mitotic figures in digitalised images. Using reliable and reproducible morphological criteria can provide the highest degree of concordance among pathologists and could even benefit the further application of artificial intelligence (AI) in breast pathology, and this relies mainly on the explicit description of these figures. In this review, we highlight the morphology of mitotic figures and their mimickers, address the current caveats in counting mitoses in breast pathology and describe how to strictly apply the morphological criteria for accurate and reliable histological grade and AI models.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Immunohistochemical Evaluation of FGD3 Expression: A New Strong Prognostic Factor in Invasive Breast Cancer

Among new prognostic factors for breast cancer, the most promising one seems to be FGD3 (Facio-Genital Dysplasia 3) gene, whose expression improves outcome by inhibiting cell migration. The aim of the study was to evaluate the prognostic role of FGD3 in invasive breast cancer in a series of 401 women, treated at our unit, by evaluating the expression of this gene by immunohistochemistry. Patients with high FGD3 expression showed a significantly better disease-free survival (DFS) (p < 0.001) and overall survival (OS) (p < 0.001). The prognostic value of FGD3 expression was stronger than that of classical pathologic parameters such as histological grade of differentiation, Ki-67 index and molecular subtype. By multivariate Cox analysis, FGD3 expression was confirmed as significant and independent prognostic factor, ranking second after age at diagnosis (≤40 years) for DFS (p = 0.003) and the second strongest predictor of OS, after AJCC Stage (p < 0.001). Our data suggest that inclusion of FGD3 evaluation in the routine workup of breast cancer patients may result in a more accurate stratification of the individual risk. The possibility to assess FGD3 expression by a simple and cheap technique such as immunohistochemistry may enhance the spread of its use in the clinical practice.

Invasive lobular carcinoma: clinicopathological features and subtypes

Objective

To analyze the characteristics of invasive lobular carcinoma (ILC) compared with invasive ductal carcinoma (IDC) and to investigate the impact of histology on axillary lymph node (ALN) involvement in luminal A subtype tumors.

Methods

We retrospectively analyzed patients diagnosed with ILC or IDC from 2012 to 2016 who underwent surgery. Patients constituted 493 primary early breast cancer cases (82 ILC; 411 IDC).

Results

Compared with IDC, ILC tumors were significantly more likely to be grade 2, estrogen receptor- (ER) positive (+), have a lower proliferation rate (Ki67 <14%), and a higher pathological T stage (pT2–4). The luminal A subtype was significantly more common in ILC compared with IDC. In a multivariate regression model, grade 2, ER+, progesterone receptor-positive, pT2, and pT3 were significantly associated with ILC. Additionally, with the luminal A subtype, ALN involvement (pathological node stage (pN)1–3) was significantly more frequent with ILC versus IDC.

Conclusions

Our data suggest that grade 2, positive hormone receptor status, and higher pathological T stage are associated with ILC. With the luminal A subtype, ALN involvement was more frequent with ILC versus IDC.

Benefit of adjuvant chemotherapy in patients with special histology subtypes of triple-negative breast cancer: a systematic review

PURPOSE

Breast cancer (BC) is a leading cause of morbidity, disability, and mortality in women, worldwide; triple-negative BC (TNBC) is a subtype traditionally associated with poorer prognosis. TNBC special histology subtypes present distinct clinical and molecular features and sensitivity to antineoplastic treatments. However, no consensus has been defined on the best adjuvant therapy. The aim of the review is to study the evidence from literature to inform the choice of adjuvant treatments in this setting.

METHODS

We systematically searched literature assessing the benefit of adjuvant chemotherapy in patients with TNBC special histotypes (PROSPERO: CRD42020153818).

RESULTS

We screened 6404 records (15 included). All the studies estimated the benefit of different chemotherapy regimens, in retrospective cohorts (median size: 69 patients (range min-max: 17-5142); median follow-up: 51 months (range: 21-268); mostly in Europe and USA). In patients with early-stage adenoid cystic TNBC, a marginal role of chemotherapy was reported. Similar for apocrine TNBC. Medullary tumors exhibited an intrinsic good prognosis with a limited role of chemotherapy, suggested to be modulated by the presence of tumor-infiltrating lymphocytes. A significant impact of chemotherapy on the overall survival was estimated in patients with metaplastic TNBC. Limitations were related to the retrospective design of all the studies and heterogeneous treatments received by the patients.

CONCLUSIONS

There is potential opportunity to consider treatment de-escalation and less intense therapies in some patients with early, special histology-type TNBC. International efforts are indispensable to validate prospective clinical decision models.

C(3)1-TAg in C57BL/6 J background as a model to study mammary tumor development

Diagnosis and prognosis of breast cancer is based on disease staging identified through histopathological and molecular biology techniques. Animal models are used to gain mechanistic insights into the development of breast cancer. C(3)1-TAg is a genetically engineered mouse model that develops mammary cancer. However, carcinogenesis caused by this transgene was characterized in the Friend Virus B (FVB) background. As most genetic studies are done in mice with C57BL/6 J background, we aimed to define the histological alterations in C3(1)-TAg C57BL/6 J animals. Our results showed that C3(1)-TAg animals with C57BL/6 J background develop solid-basaloid adenoid cystic carcinomas with increased fibrosis, decreased area of adipocytes, and a high proliferative index, which are triple-negative for progesterone, estrogen, and human epidermal growth factor receptor 2 (HER2) receptors. Our results also revealed that tumor development is slower in the C57BL/6 J background when compared with the FVB strain, providing a better model to study the different stages in breast cancer progression.

Discordance Between Immunohistochemistry and In Situ Hybridization to Detect HER2 Overexpression/Gene Amplification in Breast Cancer in the Modern Age: A Single Institution Experience and Pooled Literature Review Study

BACKGROUND

Human epidermal growth factor 2 (HER2) amplification and/or overexpression occurs in 12% to 25% of breast cancers. Accurate detection of HER2 is critical in predicting response to HER2-targeted therapy. Both immunohistochemistry (IHC) and in situ hybridization (ISH) are FDA-approved methods for detecting HER2 status because its protein overexpression is largely attributable to gene amplification. However, variable discordant results between IHC and ISH have been reported.

METHODS

We determined the frequency of HER2 IHC/ISH discordance in these patients and also performed a pooled literature review analysis.

RESULTS

Of the 1125 consecutive primary or metastatic breast cancers with HER2 IHC and ISH performed simultaneously between 2015 and 2020, 84.6% had an unequivocal HER2 status. Discordance was found in 30 cases from 26 patients, including 13 IHC^-/ISH⁺ and 17 IHC⁺/ISH^-, representing 1.6% and 11.9% of IHC^- and IHC⁺ cases, respectively. Review of the literature between 2001 and 2020 identified 46 relevant studies, with a total of 43,468 cases with IHC and ISH performed. The IHC^-/ISH+ and IHC⁺/ISH^- discordances were seen in all antibody clones and ISH methods used. The IHC⁺/ISH^- discordance was significantly higher than IHC^-/ISH⁺ (13.8% vs. 3%, P < .0001). The overall discordance constituted 4% of all cases and 5.4% of those with an unequivocal IHC status. Significantly lower incongruities for both IHC^-/ISH⁺ and IHC⁺/ISH^- were found in those published after 2018. The discordances probably reflect altered biology of HER2 oncogene/oncoprotein. Routinely performing both IHC and ISH may uncover such cases to prevent denial of potentially beneficial targeted therapy.

Breast cancer patients with a negative axillary ultrasound may have clinically significant nodal metastasis

INTRODUCTION

The non-invasive nature of the preoperative axillary ultrasound (AUS) fits the current trend of increasingly conservative axillary management. Recent publications suggest that early disease patients with clinically and radiologically negative axillae do not require sentinel lymph node biopsy (SLNB). This study aims to determine the true extent of axillary node disease in negative preoperative AUS patients.

METHODS

A 10-year breast cancer registry was reviewed to identify women with pathologically confirmed T1-2 invasive breast cancer and a negative preoperative AUS. Patients who received neoadjuvant chemotherapy were excluded. Combined positive lymph node count of SLNB ± ALND was used to determine total nodal burden (TNB). Axillae were classified into low nodal burden (LNB) defined as 1-2 positive nodes and high nodal burden (HNB) defined as ≥ 3 positive nodes.

RESULTS

762 patients with negative AUS were included. There were 46.9% and 53.0% T1 and T2 tumours, respectively. 76.9% were node negative (0 LN +), 18.9% had LNB (1-2 LN +) and 4.2% had HNB (≥ 3LN +). Specifically, HNB disease was seen in 2% of T1 tumours and 6.2 % of T2 tumours with a negative AUS. In multivariate analysis, T2 strongly associated with ≥ 3 positive ALNs (OR 2.66 CI 1.09-6.51 p = 0.03) as did lymphovascular invasion (OR 3.56 CI 1.52-8.30 p =  < 0.01).

CONCLUSION

This study shows that AUS in its current form cannot exclude HNB axillary metastasis to the extent of eliminating the need for surgical staging of the axilla. This may impact axillary local-regional recurrence and disease-free survival. We caution that a negative AUS has a rate of 4.2% of HNB. Therefore, in cases of negative AUS with a T2 tumour, we advocate continued use of SLNB.

Joint analysis of expression levels and histological images identifies genes associated with tissue morphology

Histopathological images are used to characterize complex phenotypes such as tumor stage. Our goal is to associate features of stained tissue images with high-dimensional genomic markers. We use convolutional autoencoders and sparse canonical correlation analysis (CCA) on paired histological images and bulk gene expression to identify subsets of genes whose expression levels in a tissue sample correlate with subsets of morphological features from the corresponding sample image. We apply our approach, ImageCCA, to two TCGA data sets, and find gene sets associated with the structure of the extracellular matrix and cell wall infrastructure, implicating uncharacterized genes in extracellular processes. We find sets of genes associated with specific cell types, including neuronal cells and cells of the immune system. We apply ImageCCA to the GTEx v6 data, and find image features that capture population variation in thyroid and in colon tissues associated with genetic variants (image morphology QTLs, or imQTLs), suggesting that genetic variation regulates population variation in tissue morphological traits.

Characterization of estrogen receptor-low-positive breast cancer

PURPOSE

The biology of breast cancer with a low expression level (1-10%) of estrogen receptor (ER) remains a matter of confusion. The recent American Society of Oncology/College of American Pathologist Guidelines have recommended reporting such tumors as a new "ER-low-positive" category with a recommended comment to emphasize the possible overall benefit of endocrine therapies in these patients. The aim of the study was to analyze the clinicopathologic features and clinical outcomes of ER-low-positive breast cancers.

METHODS

We characterized the clinicopathologic features and survival outcomes of ER-low-positive breast cancers in our 4179 patients diagnosed from 1998 to 2018.

RESULTS

The ER-positive, ER-low-positive, and ER-negative cases in our cohort were 2982 (71.4%), 97 (2.3%), and 1100 (26.3%), respectively. ER-low-positive tumors showed similar clinicopathologic characteristics yet significantly superior prognosis when compared to ER-negative tumors, while demonstrated largely overlapping survival outcomes with ER-positive tumors in the entire cohort. In the subcohort of tumors with a PR-positive phenotype, the prognosis of ER-low-positive tumors was intermediate between that of the ER-positive and ER-negative groups. ER-low-positive/PR-positive tumors had a significantly worse prognosis than ER-positive tumors, and a trend toward favorable survival outcomes when compared to ER-negative tumors, although no significant difference was identified for the latter. In contrast, the ER-positive and ER-low-positive groups showed similar survival outcomes in the subset of tumors with a PR-negative status, both being significantly better than ER-negative tumors.

CONCLUSIONS

PR status as a surrogate marker of functional ER signaling provides critical information in this regard. These findings suggest that while ER-low-positive tumors are themselves heterogeneous, they often respond to endocrine treatment. Analysis of molecular signatures and standardization of therapeutic strategies are important to understand the biology of ER-low-positive tumors and to enable optimal treatment in the pursuit of individualized medicine.

Chemotherapy Negates the Effect of SDF1 mRNA to Distant Metastasis and Poor Overall Survival in Breast Cancer Patients

OBJECTIVE

Investigate the effect of SDF1a, nuclear, and cytoplasmic CXCR4 breast cancer tissue on metastasis and overall survival in patients with complete-chemotherapy and no-chemotherapy.

METHODS

Cohort ambidirectional design was employed with survival analysis that followed the patient's diagnosis until obtaining the outcome, distant metastasis, or death. We analyzed samples in three groups (all-patient, no-chemotherapy, and complete-chemotherapy groups).  Breast cancer cell nuclear and cytoplasm expressions of CXCR4 protein were examined using immunohistochemistry. Amplification of mRNA SDF1a of breast cancer tissue was examined using rtPCR on 131 samples from the same initial paraffin block.

RESULTS

In the distant metastasis and Overall Survival (OS) analysis, there was no correlation between cytoplasmic and nuclear CXCR4 in all-patient, no-chemotherapy, and complete-chemotherapy groups. SDF1a was significantly correlated to shorter distant metastasis and poor OS in the all-patient (p=0.004 and p=0.04, respectively) and no-chemotherapy group (p=0.008 and p=0.026, respectively). However, in the complete-chemotherapy group, SDF1a was not correlated to either metastasis (p=0.527) or OS (p=0.993), advanced stage demonstrated a strong association on shorter distant metastatic in no-chemotherapy (p=0.021) and complete-chemotherapy group (p=0.004) and also poor OS in both groups (p=0.006 and p=0.002, respectively). The hormone receptor showed a protective effect on the no-chemotherapy group's OS (p= 0.019). Meanwhile, not undergoing chemotherapy was associated with poor OS in the all-patient group (p= 0.011).

CONCLUSION

SDF1a mRNA amplification has a significant correlation with the occurrence of metastasis and OS in all-patient and no-chemotherapy group. Undergoing chemotherapy negates the effect of SDF1a for distant metastasis and OS.

The Prognostic Value of Lymph Node Involvement after Neoadjuvant Chemotherapy Is Different among Breast Cancer Subtypes

Simple Summary

Little is known about whether residual axillary disease after neoadjuvant chemotherapy carries a different prognostic value by breast cancer subtype. We retrospectively evaluated the axillary involvement (0, 1 to 3 positive nodes, ≥4 positive nodes) on surgical specimens from a cohort of 1197 patients treated with neoadjuvant chemotherapy, and analyzed its association with survival outcomes. Relapse free survival was significantly associated with the number of positive nodes, but this effect was different by breast cancer subtype (Pinteraction = 0.004). High risk patients were those with 4 or more nodes involved in the luminal subgroup, whereas patients with 1 node or more involved had a decreased prognosis in triple negative and HER2 positive breast cancer subgroups. The prognostic value of residual axillary disease should be interpreted according to breast cancer subtype to accurately stratify patients with a high risk of recurrence after neoadjuvant chemotherapy who should be offered second line therapies.

Abstract

Introduction: The three different breast cancer subtypes (Luminal, HER2-positive, and triple negative (TNBCs) display different natural history and sensitivity to treatment, but little is known about whether residual axillary disease after neoadjuvant chemotherapy (NAC) carries a different prognostic value by BC subtype. Methods: We retrospectively evaluated the axillary involvement (0, 1 to 3 positive nodes, ≥4 positive nodes) on surgical specimens from a cohort of T1-T3NxM0 BC patients treated with NAC between 2002 and 2012. We analyzed the association between nodal involvement (ypN) binned into three classes (0; 1 to 3; 4 or more), relapse-free survival (RFS) and overall survival (OS) among the global population, and according to BC subtypes. Results: 1197 patients were included in the analysis (luminal (n = 526, 43.9%), TNBCs (n = 376, 31.4%), HER2-positive BCs (n = 295, 24.6%)). After a median follow-up of 110.5 months, ypN was significantly associated with RFS, but this effect was different by BC subtype (P_interaction = 0.004), and this effect was nonlinear. In the luminal subgroup, RFS was impaired in patients with 4 or more nodes involved (HR 2.8; 95% CI [1.93; 4.06], p < 0.001) when compared with ypN0, while it was not in patients with 1 to 3 nodes (HR = 1.24, 95% CI = [0.86; 1.79]). In patients with TNBC, both 1-3N+ and ≥4 N+ classes were associated with a decreased RFS (HR = 3.19, 95% CI = [2.05; 4.98] and HR = 4.83, 95% CI = [3.06; 7.63], respectively versus ypN0, p < 0.001). Similar decreased prognosis were observed among patients with HER2-positive BC (1-3N +: HR = 2.7, 95% CI = [1.64; 4.43] and ≥4 N +: HR = 2.69, 95% CI = [1.24; 5.8] respectively, p = 0.003). Conclusion: The prognostic value of residual axillary disease should be considered differently in the 3 BC subtypes to accurately stratify patients with a high risk of recurrence after NAC who should be offered second line therapies.

Relation Between Tumor Size and Lymph Node Metastasis According to Subtypes of Breast Cancer

Purpose

Tumor size and lymph node metastasis are important factors that contribute to the progression of breast cancer. We aimed to analyze the relationship between tumor size and lymph node metastasis molecular subtype and examine the effects of nodal metastasis on overall survival (OS).

Methods

We retrospectively reviewed the data of 16,552 patients who underwent breast surgery in Samsung Medical Center between 2000 and 2015. Information on tumor size (largest diameter of the invasive component), number of positive lymph nodes, and molecular subtype were obtained. We constructed a linear regression model to evaluate the relationship between tumor size and lymph node metastasis. To determine the effect of nodal metastasis on OS, we performed a Cox proportional regression analysis with Np/T (number of metastatic lymph nodes [n]/tumor size [cm]).

Results

This study included 12,007 patients with a median follow-up of 62 months. The linear regression coefficients were 1.043 for luminal A, 1.024 for luminal B, 0.656 for HER2, and 0.435 for triple-negative breast cancer (TNBC) subtypes. No significant difference was observed in the coefficients between the luminal A and B subtypes (p = 0.797), while all other coefficients showed significant difference. After adjusting for other risk factors, the hazard ratio (HR) of Np/T for each subtype was significant for OS: luminal A (HR, 1.134; 95% confidence interval [CI], 1.097–1.171; p < 0.001), luminal B (HR, 1.049; 95% CI, 1.013–1.086; p = 0.007), HER2 (HR, 1.069; 95% CI, 1.014–1.126; p = 0.013), and TNBC (HR, 1.038; 95% CI, 1.01–1.067; p = 0.008).

Conclusion

The incidence of lymph node metastasis differed according to molecular subtype. Luminal types have higher incidence of nodal metastasis than HER2 and TNBC. The HR of Np/T was highest in luminal A subtypes and lowest in TNBC subtypes.

Histological type and typing of breast carcinomas and the WHO classification changes over time

The World Health Organization’s new classification of breast tumors has just been published. This review aims to examine the morphological categorization of breast carcinomas which is still principally based on histological features and follows the traditions of histological typing. It gives a subjective and critical view on the WHO classifications and their changes over time, and describes the changes related to some of the most common or challenging breast carcinomas: in situ carcinomas, invasive breast carcinomas of no special type, lobular, cribriform, tubular, mucinous, papillary, metaplastic carcinomas and carcinomas with medullary pattern and those with apocrine differentiation are discussed in more details. Although the 5^th edition of the classification is not perfect, it has advantages which are mentioned along with problematic issues of classifications.

Receptor conversion in metastatic breast cancer: analysis of 390 cases from a single institution

Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor-2 (HER2) status provide clinical utility in guiding therapeutic decision-making in metastatic breast cancer (BC). Increasing data have shown substantial differences between the receptor profiles of primary BCs and their paired metastases. In this study, we provide a large single center cohort to assess the frequency of receptor conversion in metastatic BC. The overall discordant rates were 18.3%, 40.3%, and 13.7% for ER, PR, and HER2, respectively. The discordance was significantly higher for PR when compared with ER and HER2. The conversion occurred significantly as a switch from positive to negative receptor status when compared with that from negative to positive for all three receptors. Semiquantitative analyses revealed a significantly decreased expression of both ER (25%) and PR (57%) in the metastases. There was a higher rate of PR discordance in bone metastases when comparing to other common organs of relapse. Furthermore, in the subset of patients with a single primary and multiple distant metastases, the discordant rates among the distant sites were 27.5%, 39.4%, and 14.3% for ER, PR, and HER2, respectively. A positive ER status, be it in primary or metastatic BC, was associated with a prolonged metastasis-free survival when compared with ER-negative primary tumors without conversion. Furthermore, a positive ER status in metastatic BC regardless of primary was associated with a superior overall survival when compared with an ER-negative tumor without conversion. Thus, receptor conversion is a frequent event in the course of BC progression, and can also be seen between different metastatic sites. Moreover, some conversions are of prognostic significance. The findings may reflect tumor heterogeneity, sampling or treatment effect, but may also indicate alteration in tumor biology. Repeat biomarker testing is warranted in making appropriate treatment plans in the pursuit of precision medicine.

Improved detection of sentinel lymph node metastases allows reliable intraoperative identification of patients with extended axillary lymph node involvement in early breast cancer

An improved procedure that allows accurate detection of negative sentinel lymph node (SLN) and of SLN macrometastases during surgery would be highly desirable in order to protect patients from further surgery and to avoid unnecessary costs. We evaluated the accuracy of an intraoperative procedure that combines touch imprint cytology (TIC) and subsequent frozen section (FS) analysis. 2276 SLNs from 1072 patients with clinical node-negative early breast cancer were evaluated during surgery using TIC. Only cytologically-positive SLN were subsequently analysed with a single FS, preserving cytologically-negative SLN for the final postoperative histological diagnosis. Sensitivity, specificity and the accuracy of this approach were analysed by comparing the results from intra- and postoperative SLN and axillary node evaluation. This intraoperative method displayed 100% specificity for SLN metastases and was significantly more sensitive for prognostically relevant macrometastases (85%) than for micrometastases (10%). Sensitivity was highest for patients with two or more positive LNs (96%) than for those with only one (72%). 98% of the patients with final pN2a-pN3a were already identified during surgery. Patients who received primary axillary lymph node dissection had significantly more frequent metastases in further LNs (44.6%). Sensitivity was highest for patients with luminal-B, HER2+ and triple negative breast cancer and for any subtype if Ki-67 > 40%. TIC and subsequent FS of cytologically-positive SLNs is highly reliable for detection of SLN macrometastases, and allows accurate identification of patients with a high risk of extended axillary involvement during surgery, as well as accurate histological diagnosis of negative SLN.

Correlation of expression of hormone and HER2 receptors with various clinico-pathological prognostic parameters and with each other in malignant breast lesion

BACKGROUND

Estrogen receptors (ER), progesterone receptors (PR) and the human epidermal growth factor receptor-2 (HER2) are basic breast cancer molecular markers that are also best recognized prognostic factors and predictors of type of targeted therapy to be given. The objectives are to study the correlation of expression of hormone and HER2receptors with various clinico-pathological prognostic parameters like patient's age at diagnosis, menopausal status, tumor size, histological grade and lymph node status of tumor and with each other in malignant breast lesion.

METHODS

For this study histopathology (HP) and immunohistochemistry (IHC) slides of excised specimens of 330 female patients with a palpable breast lump deposited to the pathology department of a hospital as a part of routine diagnostic procedure, were evaluated under the guidance of trained doctors who have minimum 5 years of experience in oncopathology. The author has no direct involvement with patients, informed consent was not necessary and data were collected after getting permission from concerned authority.

RESULTS

This study finds significant relationship between hormone receptors and all clinico-pathological prognostic parameters taken for comparison except age at diagnosis. HER2 status has significant relationship with all clinico-pathological prognostic parameters; hormone and HER2 status suggests an inverse relationship.

CONCLUSIONS

Mien of hormone receptors expression in breast cancer is related with better prognostic factors such as older age, postmenopausal status, smaller tumor size, low histological grade and negative lymph node status, however the opposite is correct for HER2. Hormone receptors and HER2 have an inversely proportionate relationship with each other.

Tumor size as a predictor of lymphatic invasion in oral melanomas of dogs

OBJECTIVE

To investigate putative associations between oral melanoma size and variables of histologic grade such as mitotic index, nuclear atypia, junctional activity, ulceration, lymphatic invasion, and degree of pigmentation.

SAMPLE

59 samples of oral melanomas from dogs sourced from 6 diagnostic laboratories within Australia.

PROCEDURES

The size of each melanoma was microscopically measured, and each sample was evaluated for variables of histologic grade including mitotic index, nuclear atypia, junctional activity, ulceration, lymphatic invasion, and degree of pigmentation by a veterinary pathologist. The association between tumor size and histologic outcomes was then statistically evaluated.

RESULTS

A significant relationship was identified between the size of oral melanomas and a single variable of histologic grade, lymphatic invasion, with larger tumors more likely to show lymphatic invasion. Further analysis revealed 2 applicable size thresholds for different clinical scenarios. Results indicated lymphatic invasion can confidently be ruled out for tumors < 6.5 mm in diameter (100% sensitivity) and ruled in for tumors ≥ 24.5 mm in diameter (100% specificity).

CONCLUSIONS AND CLINICAL RELEVANCE

An association was found for oral melanomas of dogs between tumor size and lymphatic invasion.

The Evolution of Our Understanding of the Biology of Cancer Is the Key to Avoiding Overdiagnosis and Overtreatment

There has been a tremendous evolution in our thinking about cancer since the 1880s. Breast cancer is a particularly good example to evaluate the progress that has been made and the new challenges that have arisen due to screening that inadvertently identifies indolent lesions. The degree to which overdiagnosis is a problem depends on the reservoir of indolent disease, the disease heterogeneity, and the fraction of the tumors that have aggressive biology. Cancers span the spectrum of biological behavior, and population-wide screening increases the detection of tumors that may not cause harm within the patient's lifetime or may never metastasize or result in death. Our approach to early detection will be vastly improved if we understand, address, and adjust to tumor heterogeneity. In this article, we use breast cancer as a case study to demonstrate how the approach to biological characterization, diagnostics, and therapeutics can inform our approach to screening, early detection, and prevention. Overdiagnosis can be mitigated by developing diagnostics to identify indolent disease, incorporating biology and risk assessment in screening strategies, changing the pathology rules for tumor classification, and refining the way we classify precancerous lesions. The more the patterns of cancers can be seen across other cancers, the more it is clear that our approach should transcend organ of origin. This will be particularly helpful in advancing the field by changing both our terminology for what is cancer and also by helping us to learn how best to mitigate the risk of the most aggressive cancers.See all articles in this CEBP Focus section, "NCI Early Detection Research Network: Making Cancer Detection Possible."

One-year conditional survival of dogs and cats with invasive mammary carcinomas: A concept inspired from human breast cancer

Numerous studies have described the prognostic factors of canine and feline mammary carcinomas (MCs), that is, variables that predict patient survival after diagnosis. But how does survival estimation evolve in patients that escaped early death from their cancer? In human oncology, conditional survival (CS), the probability of surviving X further years when cancer patients have already survived Y years, is used to analyse cancer outcomes in a long‐term perspective. In this cohort of 344 dogs and 342 cats with surgically removed stage I to III invasive MCs, with a minimal follow‐up of 2 years, we calculated the 1‐year CS, that is, the probability for patients that have survived 1 year, to survive or to die from cancer during the subsequent year. The 1‐year conditional specific survival probabilities were 59% and 48% at diagnosis of invasive MC respectively in dogs and cats, and 80% and 52% in 1‐year surviving dogs and cats respectively, suggesting that 1‐year surviving dogs were relatively protected from cancer‐related death, whereas feline MCs remained life‐threatening cancers for longer periods of time. Among the most significant parameters associated with CS in surviving dogs and cats were the nodal stage and lymphovascular invasion, as well as patient age, cancer stage and margin status in surviving dogs. By comparison, tumour size and the histological grade did not significantly alter CS probabilities in surviving dogs and cats. Conditional survival may be considered a very interesting tool for veterinary practitioners to estimate the likely outcome of cancer survivors.

Prognostic impact of circumferential resection margin in esophageal cancer with or without neoadjuvant chemoradiotherapy

The prognostic impact of circumferential resection margin (CRM) in surgically resected esophageal squamous cell carcinoma (ESCC) has been controversial. This investigation assessed the prognostic impact of CRM in surgically resected pathologic T3 ESCC patients with or without neoadjuvant chemoradiotherapy (nCRT). We reviewed consecutive p/yp T3 ESCC patients undergoing esophagectomy from two medical centers between January 2009 and December 2016. The cohort was divided into two groups: upfront esophagectomy (upfront surgery) and nCRT followed by esophagectomy (nCRT + surgery). CRM status was assessed and divided into CRM > 1 mm, 0 < CRM < 1 mm, and tumor at CRM. A total of 217 p/yp T3 ESCC patients undergoing esophagectomy (138 patients in the upfront surgery group and 79 in the nCRT + surgery group) were enrolled. In the upfront surgery group, patients with 0 < CRM < 1 mm showed equivalent overall survival to those with CRM > 1 mm (log-rank P = 0.817) and significantly outlived those with tumor at CRM (log-rank P < 0.001). However, in the nCRT + surgery group, CRM > 1 mm failed to show survival superiority to CRM between 0 and 1 mm or involved by cancer (log-rank P = 0.390). In conclusion, a negative CRM, even though being <1 mm, is adequate for pT3 ESCC patients undergoing upfront esophagectomy. In contrast, the CRM status is less prognostic in ypT3 ESCC patients undergoing nCRT followed by esophagectomy.