Breast Cancer in Younger and Older Women: A Comparison of Clinicopathological Traits.

Breast cancer stands as the prevailing invasive cancer globally, bearing high mortality rates among women. Existing evidence indicates diminished survival rates in younger patients. Consequently, this study endeavors to assess and contrast the pathological features of breast cancer in women under 40 years of age with their older counterparts. Conducted as a cross-sectional analysis, this study encompasses 560 patients diagnosed with breast cancer, seeking treatment at Mymensingh Medical College Hospital (MMCH), Community Based Medical College Bangladesh (CBMCB) and several private hospitals in Mymensingh. The gathered data incorporates information such as age, residential area, occupation, tumor histopathology, TNM classification, staging and status of hormone receptor. The patients' mean age (standard deviation) was 49.7±11.9 years, with 20.5% below 40, most were from rural areas and were housewives. Ductal carcinoma prevailed as the most common histopathologic type (87.67%). However, younger patients exhibited a higher prevalence of lobular and other rare carcinomas compared to their older counterparts (p=0.04). Additionally, the younger group demonstrated larger tumor sizes (p=0.01), lymphatic node involvement (p=0.04) and advanced staging (p=0.004). Notably, younger age showed more negativity for estrogen and/or progesterone receptors. The results suggested that women under 40 years old exhibit more aggressive tumor characteristics and a more severe form of breast cancer compared to their older counterparts.

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal carcinoma In Situ is safe (E. S. Hwang et al., BMJ Open, 9: e026797, 2019, A. Francis et al., Eur J Cancer. 51: 2296-2303, 2015, Chizuko Kanbayashi et al. The international collaboration of active surveillance trials for low-risk DCIS (LORIS, LORD, COMET, LORETTA),  L. E. Elshof et al., Eur J Cancer, 51, 1497-510, 2015). Low-risk is defined as grade I or II DCIS. Because DCIS grade is a major eligibility criteria in these trials, it would be very helpful to assess DCIS grade on mammography, informed by grade assessed on DCIS histopathology in pre-surgery biopsies, since surgery will not be performed on a significant number of patients participating in these trials. OBJECTIVE: To assess the performance and clinical utility of a convolutional neural network (CNN) in discriminating high-risk (grade III) DCIS and/or Invasive Breast Cancer (IBC) from low-risk (grade I/II) DCIS based on mammographic features. We explored whether the CNN could be used as a decision support tool, from excluding high-risk patients for active surveillance. METHODS: In this single centre retrospective study, 464 patients diagnosed with DCIS based on pre-surgery biopsy between 2000 and 2014 were included. The collection of mammography images was partitioned on a patient-level into two subsets, one for training containing 80% of cases (371 cases, 681 images) and 20% (93 cases, 173 images) for testing. A deep learning model based on the U-Net CNN was trained and validated on 681 two-dimensional mammograms. Classification performance was assessed with the Area Under the Curve (AUC) receiver operating characteristic and predictive values on the test set for predicting high risk DCIS-and high-risk DCIS and/ or IBC from low-risk DCIS. RESULTS: When classifying DCIS as high-risk, the deep learning network achieved a Positive Predictive Value (PPV) of 0.40, Negative Predictive Value (NPV) of 0.91 and an AUC of 0.72 on the test dataset. For distinguishing high-risk and/or upstaged DCIS (occult invasive breast cancer) from low-risk DCIS a PPV of 0.80, a NPV of 0.84 and an AUC of 0.76 were achieved. CONCLUSION: For both scenarios (DCIS grade I/II vs. III, DCIS grade I/II vs. III and/or IBC) AUCs were high, 0.72 and 0.76, respectively, concluding that our convolutional neural network can discriminate low-grade from high-grade DCIS.

[A Patient with Cancer of Unknown Primary Who Responded to Chemotherapy].

Cancer of unknown primary is a class of malignant tumors, histologically identified as metastatic lesions whose primary origin is unknown despite adequate investigations for the primary tumor. Although the prognosis of cancer of unknown primary is generally poor, here, we report our experience with a patient who responded to chemotherapy. The patient was a 78-year-old woman. She had a history of gastric cancer at the age of 76 years. In June of year X-1, she was diagnosed with gastric cancer(tub1>tub2, pT1bN0M0, pStage Ⅰa)and underwent distal gastrectomy. One year after surgery, computed tomography revealed right supraclavicular lymphadenopathy, for which cervical lymphadenectomy was performed. The pathological diagnosis was ductal carcinoma with comedo necrosis and poorly differentiated solid adenocarcinoma that were suggestive of metastases from breast cancer. However, a detailed examination of the mammary glands revealed no mass. Imaging studies led to a diagnosis of cancer of unknown primary. Therefore, chemotherapy, according to the treatment of pancreatic cancer, was planned based on immunostaining, tumor markers, etc. Chemotherapy response evaluation after completing 4 courses demonstrated a partial response; the patient responded to the chemotherapy. We considered that estimating primary lesions from histopathological images, tumor markers, etc., may help determine effective chemotherapy regimens.

[A Case of Synchronous Papillary Thyroid Cancer and Breast Ductal Cancer].

Occurrences of thyroid cancer and breast cancer metachronously or synchronously are common for women. Explanations for these associations include detection bias, shared hormonal risk factors, and genetic susceptibility, but the etiology behind specific associations is not elucidated well. The importance of the relationship between breast and thyroid cancer will continue to become evident and physicians should be aware of this association in caring for thyroid and breast cancer survivors. We report a case of synchronous papillary thyroid cancer and breast ductal cancer.

Male ductal carcinoma in situ: diagnosis and management of a rare disease in men.

Ductal carcinoma in situ is very rare in male patients, accounting for approximately 5%-7% of all male breast cancers. We present a case of a man in his early 70s who presented with bloody nipple discharge and gynaecomastia and was subsequently diagnosed with ductal carcinoma in situ (DCIS). We discuss his management with surgical resection and the consideration of adjuvant treatment. We also review the existing literature on the presentation, diagnosis and management of DCIS in men.

Determination of Factors Associated with Upstage in Atypical Ductal Hyperplasia to Identify Low-Risk Patients Where Active Surveillance May be an Alternative.

BACKGROUND: Excision is routinely recommended for atypical ductal hyperplasia (ADH) found on core biopsy given cancer upstage rates of near 20%. Identifying a cohort at low-risk for upstage may avoid low-value surgery. Objectives were to elucidate factors predictive of upstage in ADH, specifically near-complete core sampling, to potentially define a group at low upstage risk. PATIENTS AND METHODS: This retrospective, cross-sectional, multi-institutional study from 2015 to 2019 of 221 ADH lesions in 216 patients who underwent excision or active observation (≥ 12 months imaging surveillance, mean follow-up 32.6 months) evaluated clinical, radiologic, pathologic, and procedural factors for association with upstage. Radiologists prospectively examined imaging for lesional size and sampling proportion. RESULTS: Upstage occurred in 37 (16.7%) lesions, 25 (67.6%) to ductal carcinoma in situ (DCIS) and 12 (32.4%) to invasive cancer. Factors independently predictive of upstage were lesion size ≥ 10 mm (OR 5.47, 95% CI 2.03-14.77, p < 0.001), pathologic suspicion for DCIS (OR 12.29, 95% CI 3.24-46.56, p < 0.001), and calcification distribution pattern (OR 8.08, 95% CI 2.04-32.00, p = 0.003, "regional"; OR 19.28, 95% CI 3.47-106.97, p < 0.001, "linear"). Near-complete sampling was not correlated with upstage (p = 0.64). All three significant predictors were absent in 65 (29.4%) cases, with a 1.5% upstage rate. CONCLUSIONS: The upstage rate among 221 ADH lesions was 16.7%, highest in lesions ≥ 10 mm, with pathologic suspicion of DCIS, and linear/regional calcifications on mammography. Conversely, 30% of the cohort exhibited all low-risk factors, with an upstage rate < 2%, suggesting that active surveillance may be permissible in lieu of surgery.

Clinicopathological analysis of 38 male patients diagnosed with breast cancer.

BACKGROUND: Male breast cancer (MBC) accounts for one percent of all breast cancers. Due to the lack of awareness and routine screening programs, most patients present with systemic disease at the time of diagnosis with low overall survival. OBJECTIVES: This study aims to investigate the prognostic factors of male breast cancer and its correlation with established prognostic parameters and patient outcomes. METHODS: Thirty-eight male breast cancer patients are identified from the MKA Breast Cancer Clinic database, and their corresponding clinical and pathological characteristics are obtained. Cut-off values of 1% and 10% are applied to further classify ER and PR results. RESULTS: Older men are more likely to develop MBC than younger men and are more likely to have spread to axillary lymph nodes. Invasive ductal carcinoma is a more common histologic type in MBC. All the tested patients have ER and PR positivity. Distant metastasis developed in 17/38 (44.7%) patients. Bone metastasis is seen commonly in metastatic MBC. CONCLUSIONS: According to our cohort, MBC is seen in older males, presents in later stages, and shows hormone receptor positivity and a tendency to bone involvement. MBC is a heterogenous but distinct biological entity requiring a specific clinical and pathological approach.

Metastatic profiles and survival differences between infiltrating ductal carcinoma and infiltrating lobular carcinoma in invasive breast cancer.

BACKGROUND: In this study, we conducted a comprehensive evaluation of metastatic profiles and survival outcomes in patients with infiltrating ductal carcinoma (IDC) and infiltrating lobular carcinoma (ILC) treated at our university hospital center. METHODS: We collected and analyzed data from all patients diagnosed with invasive breast cancer at our center between January 1, 2007, and 31 December 2014. We specifically compared three subgroups: patients with IDC, patients with ILC and patients with mixed carcinoma, which is a combination of IDC and ILC. RESULTS: Among the 1963 patients treated for invasive breast cancer in our center during the study period, 1435 had IDC, 466 had ILC, and 59 had mixed carcinoma. The incidence of patients with at least one positive axillary lymph node differed significantly: 40 % for IDC, 36 % for ILC, and 45 % for mixed carcinoma (p = 0.001). However, there was no significant difference in the mean number of positive nodes (p = 0.1633). The occurrence of distant metastases was lower in patients with ILC (p = 0.04), particularly in the case of brain metastases (p = 0.01), although there was no difference in bone or visceral metastatic sites. Patients with ILC exhibited a longer mean time to metastasis from the initial diagnosis of invasive breast carcinoma. Overall survival (p = 0.0525) and survival without locoregional recurrence (p = 0.026) were significantly different. Specifically, the 5-year overall survival rates for IDC, ILC, and mixed carcinoma were approximately 95 %. Distance metastatic-free survival at 5 years was 85 % for IDC, 91 % for ILC, and 87 % for mixed carcinoma (p = 0.00506). CONCLUSION: Our findings indicate variations in the distribution of distant metastatic sites among patients with IDC, ILC, and mixed carcinoma, as well as differences in survival outcomes. This study sheds light on the unique characteristics and clinical implications associated with these two distinct subtypes of invasive breast cancer.

The type 2 inflammatory response favors recognition of tumor antigens by IgE in breast cancer.

BACKGROUND: Several studies describe an inverse statistical relationship between the presence of an allergy and development of cancer. However, the immunological mechanism involved in the relationship between these two degenerative diseases has not been explored. AIMS: The main objective of this study was to explore the possibility that the lymphocyte T helper (Th) 2 response, a characteristic of allergy, induces recognition of tumor antigens. METHODS AND RESULTS: Patients with a clinical diagnosis of breast ductal carcinoma were included. Histopathological markers related to proliferation of tumor cells were determined (Her-2-neu, Ki-67, estrogen receptor, and progesterone receptor). IHC was performed using IgE antibodies purified from an allergy patient and from each biopsy donor patient. Serum concentrations of cytokines representative of Th1 and Th2 inflammatory responses were determined. A total of 14 patients with a confirmed diagnosis of breast ductal carcinoma were included. IHC performed on biopsies showed a weak response when using purified IgE antibodies from an allergy patient; however, IHC using the IgE of each patient as the primary antibody showed an intense and highly specific signal. Serum concentrations of cytokines of the Th2 response, that is, IL-4 (130.5 pg/mL (116-135 pg/mL)), IL-5 (202 pg/mL (191-213 pg/mL)), and IL-13 (105.5 pg/mL (98-117 pg/mL)), were significantly higher than those of the Th1 response, that is, IL-6 (86 pg/mL (79-90 pg/mL)) and INF-γ (93 pg/mL (79-99 pg/mL)). CONCLUSION: Purified IgE antibodies specifically recognize tumor cells in breast ductal carcinoma.

Genomic disparity impacts variant classification of cancer susceptibility genes in Turkish breast cancer patients.

OBJECTIVE: Turkish genome is underrepresented in large genomic databases. This study aims to evaluate the effect of allele frequency in the Turkish population in determining the clinical utility of germline findings in breast cancer, including invasive lobular carcinoma (ILC), mixed invasive ductal and lobular carcinoma (IDC-L), and ductal carcinoma (DC). METHODS: Two clinic-based cohorts from the Umraniye Research and Training Hospital (URTH) were used in this study: a cohort consisting of 132 women with breast cancer and a non-cancer cohort consisting of 492 participants. The evaluation of the germline landscape was performed by analysis of 27 cancer genes. The frequency and type of variants in the breast cancer cohort were compared to those in the non-cancer cohort to investigate the effect of population genetics. The variant allele frequencies in Turkish Variome and gnomAD were statistically evaluated. RESULTS: The genetic analysis identified 121 variants in the breast cancer cohort (actionable = 32, VUS = 89) and 223 variants in the non-cancer cohort (actionable = 25, VUS = 188). The occurrence of 21 variants in both suggested a possible genetic population effect. Evaluation of allele frequency of 121 variants from the breast cancer cohort showed 22% had a significantly higher value in Turkish Variome compared to gnomAD (p < 0.0001, 95% CI) with a mean difference of 60 times (ranging from 1.37-354.4). After adjusting for variant allele frequency using the ancestry-appropriate database, 6.7% (5/75) of VUS was reclassified to likely benign. CONCLUSION: To our knowledge, this is the first study of population genetic effects in breast cancer subtypes in Turkish women. Our findings underscore the need for a large genomic database representing Turkish population-specific variants. It further highlights the significance of the ancestry-appropriate population database for accurate variant assessment in clinical settings.

Immune cell infiltrate in ductal carcinoma in situ and the risk of dying from breast cancer: case-control study.

BACKGROUND: Studies identifying risk factors for death from breast cancer after ductal carcinoma in situ (DCIS) are rare. In this retrospective nested case-control study, clinicopathological factors in women treated for DCIS and who died from breast cancer were compared with those of patients with DCIS who were free from metastatic disease. METHODS: The study included patients registered with DCIS without invasive carcinoma in Sweden between 1992 and 2012. This cohort was linked to the National Cause of Death Registry. Of 6964 women with DCIS, 96 were registered with breast cancer as cause of death (cases). For each case, up to four controls (318; women with DCIS, alive and without metastatic breast cancer at the time of death of the corresponding case) were selected randomly by incidence density sampling. Whole slides of tumour tissue were evaluated for DCIS grade, comedo necrosis, and intensity of periductal lymphocytic infiltrate. Composition of the immune cell infiltrate, expression of oestrogen receptor, progesterone receptor, human epidermal growth factor receptor 2, and proliferation marker Ki-67 were scored on tissue microarrays. Clinical information was obtained from medical records. Information on date, site, and histological characteristics of local and distant recurrences was obtained from medical records for both cases and controls. RESULTS: Tumour tissue was analysed from 65 cases and 195 controls. Intense periductal lymphocytic infiltrate around DCIS was associated with an increased risk of later dying from breast cancer (OR 2.21. 95% c.i. 1.01 to 4.84). Tumours with more intense lymphocytic infiltrate had a lower T cell/B cell ratio. None of the other biomarkers correlated with increased risk of breast cancer death. CONCLUSION: The immune response to DCIS may influence the risk of dying from breast cancer.

Synchronous double primary small cell lung cancer and invasive ductal breast carcinoma: a case report.

BACKGROUND: Although lung and breast cancers are common malignancies, the occurrence of primary synchronous neoplasms involving these organs has been rarely reported in literature. CASE PRESENTATION: A 75-year-old female patient presented at a local hospital with a ten-day history of dizziness and slurred speech. A CT contrast-enhanced scan revealed a 4.2 cm mass in the lower lobe of the right lung and a 3.8 cm space-occupying lesion in the right breast. Subsequent breast ultrasound identified a hypoechoic lesion measuring5.41 × 4.75 × 3.06 cm in the right breast, and an ultrasound-guided biopsy confirmed the presence of infiltrating ductal carcinoma of the right breast. The immunohistochemistry analysis of the breast mass revealed positive staining for ER, PR, HER-2, AR and Ki67 in the tumor cells, while negative staining was observed for P63, Calponin, CK5/6 and CK14. MR imaging of the head detected abnormal signals in the right frontal lobe (3.6 cm×2.9 cm in size), left cerebellar hemisphere, and punctate enhancement in the left temporal lobe, indicating potential metastasis. Pathological examination of a lung biopsy specimen confirmed the presence of small cell lung cancer (SCLC). Furthermore, immunohistochemistry analysis of the lung lesions demonstrated positive staining for TTF-1, CK-Pan, Syn, CgA, CD56, P53 (90%) and Ki67 (70%), and negative staining for NapsinA and P40 in the tumor cells. The patient's diagnosis of SCLC with stage cT2bN0M1c IVB and brain metastases (BM), as well as invasive ductal breast carcinoma (IDC), was confirmed based on the aforementioned results. Whereupon we proposed a treatment plan consisting of whole-brain radiation (40 Gy/20fractions), focal radiotherapy (60 Gy/20fractions), and adjuvant concurrent chemotherapy with oral etoposide (50 mg on days 1 to 20). CONCLUSIONS: To the best of our knowledge, the present case is the first of its kind to describe the synchronous double cancer, consisting of primary SCLC and IDC.

Sonography-based multimodal information platform for identifying the surgical pathology of ductal carcinoma in situ.

BACKGROUND: The risk of ductal carcinoma in situ (DCIS) identified by biopsy often increases during surgery. Therefore, confirming the DCIS grade preoperatively is necessary for clinical decision-making. PURPOSE: To train a three-classification deep learning (DL) model based on ultrasound (US), combining clinical data, mammography (MG), US, and core needle biopsy (CNB) pathology to predict low-grade DCIS, intermediate-to-high-grade DCIS, and upstaged DCIS. MATERIALS AND METHODS: Data of 733 patients with 754 DCIS cases confirmed by biopsy were retrospectively collected from May 2013 to June 2022 (N1), and other data (N2) were confirmed by biopsy as low-grade DCIS. The lesions were randomly divided into training (n=471), validation (n=142), and test (n = 141) sets to establish the DCIS-Net. Information on the DCIS-Net, clinical (age and sign), US (size, calcifications, type, breast imaging reporting and data system [BI-RADS]), MG (microcalcifications, BI-RADS), and CNB pathology (nuclear grade, architectural features, and immunohistochemistry) were collected. Logistic regression and random forest analyses were conducted to develop Multimodal DCIS-Net to calculate the specificity, sensitivity, accuracy, receiver operating characteristic curve, and area under the curve (AUC). RESULTS: In the test set of N1, the accuracy and AUC of the multimodal DCIS-Net were 0.752-0.766 and 0.859-0.907 in the three-classification task, respectively. The accuracy and AUC for discriminating DCIS from upstaged DCIS were 0.751-0.780 and 0.829-0.861, respectively. In the test set of N2, the accuracy and AUC of discriminating low-grade DCIS from upstaged low-grade DCIS were 0.769-0.987 and 0.818-0.939, respectively. DL was ranked from one to five in the importance of features in the multimodal-DCIS-Net. CONCLUSION: By developing the DCIS-Net and integrating it with multimodal information, diagnosing low-grade DCIS, intermediate-to high-grade DCIS, and upstaged DCIS is possible. It can also be used to distinguish DCIS from upstaged DCIS and low-grade DCIS from upstaged low-grade DCIS, which could pave the way for the DCIS clinical workflow.

Tumor microenvironment and immune system preservation in early-stage breast cancer: routes for early recurrence after mastectomy and treatment for lobular and ductal forms of disease.

BACKGROUND: Intra-ductal cancer (IDC) is the most common type of breast cancer, with intra-lobular cancer (ILC) coming in second. Surgery is the primary treatment for early stage breast cancer. There are now irrefutable data demonstrating that the immune context of breast tumors can influence growth and metastasis. Adjuvant chemotherapy may be administered in patients who are at a high risk of recurrence. Our goal was to identify the processes underlying both types of early local recurrences. METHODS: This was a case-control observational study. Within 2 years of receiving adjuvant taxan and anthracycline-based chemotherapy, as well as modified radical mastectomy (MRM), early stage IDC and ILC recurred. Vimentin, α-smooth muscle actin (SMA), platelet-derived growth factor (PDGF), matrix metalloproteinase (MMP1), and clustered differentiation (CD95) were investigated. RESULTS: Of the samples in the ductal type group, 25 showed local recurrence, and 25 did not. Six individuals in the lobular-type group did not experience recurrence, whereas seven did. Vimentin (p = 0.000 and 0.021), PDGF (p = 0.000 and 0.002), and CD95 (p = 0.000 and 0.045) expressions were significantly different in ductal and lobular carcinoma types, respectively. Measurement of ductal type was the sole significant difference found in MMP1 (p = 0.000) and α-SMA (p = 0.000). α-SMA and CD95 were two variables that helped the recurrence mechanism in the ductal type according to the pathway analysis. In contrast, the CD95 route is a recurrent mechanism for the lobular form. CONCLUSIONS: While the immune system plays a larger role in ILC, the tumor microenvironment and immune system both influence the recurrence of IDC. According to this study, improving the immune system may be a viable cancer treatment option.

Improving the diagnosis of ductal carcinoma in situ with microinvasion without immunohistochemistry: An innovative method with H&E-stained and multiphoton microscopy images.

Ductal carcinoma in situ with microinvasion (DCISM) is a challenging subtype of breast cancer with controversial invasiveness and prognosis. Accurate diagnosis of DCISM from ductal carcinoma in situ (DCIS) is crucial for optimal treatment and improved clinical outcomes. However, there are often some suspicious small cancer nests in DCIS, and it is difficult to diagnose the presence of intact myoepithelium by conventional hematoxylin and eosin (H&E) stained images. Although a variety of biomarkers are available for immunohistochemical (IHC) staining of myoepithelial cells, no single biomarker is consistently sensitive to all tumor lesions. Here, we introduced a new diagnostic method that provides rapid and accurate diagnosis of DCISM using multiphoton microscopy (MPM). Suspicious foci in H&E-stained images were labeled as regions of interest (ROIs), and the nuclei within these ROIs were segmented using a deep learning model. MPM was used to capture images of the ROIs in H&E-stained sections. The intensity of two-photon excitation fluorescence (TPEF) in the myoepithelium was significantly different from that in tumor parenchyma and tumor stroma. Through the use of MPM, the myoepithelium and basement membrane can be easily observed via TPEF and second-harmonic generation (SHG), respectively. By fusing the nuclei in H&E-stained images with MPM images, DCISM can be differentiated from suspicious small cancer clusters in DCIS. The proposed method demonstrated good consistency with the cytokeratin 5/6 (CK5/6) myoepithelial staining method (kappa coefficient = 0.818).

Deep-learning model to improve histological grading and predict upstaging of atypical ductal hyperplasia / ductal carcinoma in situ on breast biopsy.

AIMS: Risk stratification of atypical ductal hyperplasia (ADH) and ductal carcinoma in situ (DCIS), diagnosed using breast biopsy, has great clinical significance. Clinical trials are currently exploring the possibility of active surveillance for low-risk lesions, whereas axillary lymph node staging may be considered during surgical planning for high-risk lesions. We aimed to develop a machine-learning algorithm based on whole-slide images of breast biopsy specimens and clinical information to predict the risk of upstaging to invasive breast cancer after wide excision. METHODS AND RESULTS: Patients diagnosed with ADH/DCIS on breast biopsy were included in this study, comprising 592 (740 slides) and 141 (198 slides) patients in the development and independent testing cohorts, respectively. Histological grading of the lesions was independently evaluated by two pathologists. Clinical information, including biopsy method, lesion size, and Breast Imaging Reporting and Data System (BI-RADS) classification of ultrasound and mammograms, were collected. Deep DCIS consisted of three deep neural networks to evaluate nuclear grade, necrosis, and stromal reactivity. Deep DCIS output comprised five parameters: total patches, lesion extent, Deep Grade, Deep Necrosis, and Deep Stroma. Deep DCIS highly correlated with the pathologists' evaluations of both slide- and patient-level labels. All five parameters of Deep DCIS were significantly associated with upstaging to invasive carcinoma in subsequent wide excisional specimens. Using multivariate logistic regression, Deep DCIS predicted upstaging to invasive carcinoma with an area under the curve (AUC) of 0.81, outperforming pathologists' evaluation (AUC, 0.71 and 0.69). After including clinical and hormone receptor status information, performance further improved (AUC, 0.87). This combined model retained its predictive power in two subgroup analyses: the first subgroup included unequivocal DCIS (excluding cases of ADH and DCIS suspicious for microinvasion) (AUC, 0.83), while the second excluded cases of high-grade DCIS (AUC, 0.81). The model was validated in an independent testing cohort (AUC, 0.81). CONCLUSION: This study demonstrated that deep-learning models can refine histological evaluation of ADH and DCIS on breast biopsies, which may help guide future treatment planning.

Potential role of Fbxo22 in resistance to endocrine therapy in breast cancer with invasive lobular carcinoma.

BACKGROUND: Invasive lobular carcinoma (ILC) is distinct from invasive ductal carcinoma (IDC) in terms of their hormonal microenvironments that may require different therapeutic strategies. We previously reported that selective estrogen receptor modulator (SERM) function requires F-box protein 22 (Fbxo22). Here, we investigated the role of Fbxo22 as a potential biomarker contributing to the resistance to endocrine therapy in ILC. METHODS: A total of 302 breast cancer (BC) patients including 150 ILC were recruited in the study. Fbxo22 expression and clinical information were analyzed to elucidate whether Fbxo22 negativity could be a prognostic factor or there were any correlations among clinical variables and SERM efficacy. RESULTS: Fbxo22 negativity was significantly higher in ILC compared with IDC (58.0% vs. 27.0%, P < 0.001) and higher in postmenopausal patients than premenopausal patients (64.1% vs. 48.2%, P = 0.041). In the ILC cohort, Fbxo22-negative patients had poorer overall survival (OS) than Fbxo22-positive patients, with 10-year OS rates of 77.4% vs. 93.6% (P = 0.055). All patients treated with SERMs, Fbxo22 negativity resulted in a poorer outcome, with 10-year OS rates of 81.3% vs. 92.3% (P = 0.032). In multivariate analysis regarding recurrence-free survival (RFS) in ILC patients, Fbxo22 status was independently predictive of survival as well as lymph node metastasis. CONCLUSION: Fbxo22 negativity significantly impacts on survival in BC patients with IDC and ILC, and the disadvantage was enhanced among ILC postmenopausal women or patients treated with SERMs. The findings suggest that different therapeutic strategies might be needed according to the different histopathological types when considering adjuvant endocrine therapy.

Breast surgery after neoadjuvant chemotherapy in patients with lobular carcinoma: surgical and oncologic outcome.

INTRODUCTION: Breast cancer patients with invasive lobular carcinoma (ILC) have an increased risk of positive margins after surgery and often show little response to neoadjuvant chemotherapy (NAC). We aimed to investigate surgical outcomes in patients with ILC treated with NAC. METHODS: In this retrospective cohort study, all breast cancer patients with ILC treated with NAC who underwent surgery at the Netherlands Cancer Institute from 2010 to 2019 were selected. Patients with mixed type ILC in pre-NAC biopsies were excluded if the lobular component was not confirmed in the surgical specimen. Main outcomes were tumor-positive margins and re-excision rate. Associations between baseline characteristics and tumor-positive margins were assessed, as were complications, locoregional recurrence rate (LRR), recurrence-free survival (RFS), and overall survival (OS). RESULTS: We included 191 patients. After NAC, 107 (56%) patients had breast conserving surgery (BCS) and 84 (44%) patients underwent mastectomy. Tumor-positive margins were observed in 67 (35%) patients. Fifty five (51%) had BCS and 12 (14%) underwent mastectomy (p value < 0.001). Re-excision was performed in 35 (33%) patients with BCS and in 4 (5%) patients with mastectomy. Definitive surgery was mastectomy in 107 (56%) patients and BCS in 84 (44%) patients. Tumor-positive margins were associated with cT ≥ 3 status (OR 4.62, 95% CI 1.26-16.98, p value 0.021) in the BCS group. Five-year LRR (4.7%), RFS (81%), and OS (93%) were not affected by type of surgery after NAC. CONCLUSION: Although 33% of ILC breast cancer patients undergoing BCS after NAC required re-excision for positive resection margins, it is considered safe given that five-year RFS remained excellent and LRR and OS did not differ by extent of surgery.