Invasive Ductal Carcinoma Of Breast Research Articles

Longitudinal assessment of real-world patient adherence: a 12-month electronic patient-reported outcomes follow-up of women with early breast cancer undergoing treatment

BackgroundElectronic patient-reported outcomes (ePROs) assess patients’ health status and quality of life, improving patient care and treatment effects, yet little is known about their use and adherence in routine patient care.AimsWe evaluated the adherence of invasive breast cancer and ductal carcinoma in situ (DCIS) patients to ePROs follow-up and whether specific patient characteristics are related to longitudinal non-adherence.MethodsSince November 2016, the Breast Center at Charité – Universitätsmedizin Berlin has implemented an ongoing prospective PRO routine program, requiring patients to complete ePROs assessments and consent to email-based follow-up in the first 12 months after therapy starts. Frequencies and summary statistics are presented. Multiple logistic regression models were performed to determine an association between patient characteristics and non-adherence.ResultsOut of 578 patients, 239 patients (41.3%, 95%CI: 37.3–45.5%) completed baseline assessment and all five ePROs follow-up during the first 12 months after therapy. On average, above 70% of those patients responded to the ePROs follow-up assessment. Adherence to the ePROs follow-up was higher during the COVID-19 pandemic than in the time periods before (47.4% (111/234) vs. 33.6% (71/211)). Factors associated with longitudinal non-adherence were younger age, a higher number of comorbidities, no chemotherapy, and a low physical functioning score in the EORTC QLQ-C30 at baseline.ConclusionsThe study reveals moderate adherence to 12-month ePROs follow-up assessments in invasive early breast cancer and DCIS patients, with response rates ranging from 60 to 80%. Emphasizing the benefits for young patients and those with high disease burdens might further increase adherence.

Comparison of clinical characteristics and outcomes in primary neuroendocrine breast carcinoma versus invasive ductal carcinoma

BackgroundNeuroendocrine breast carcinoma (NECB) is a rare, special histologic type of breast cancer. There are some small sample studies on the clinical outcomes of NECB patients, which are worthy of further discussion.MethodsWe conducted a retrospective case-control study of clinical characteristics and outcomes among patients with primary NECB versus invasive carcinoma of no special type (NST) between November 2004 and November 2017 in the Peking Union Medical College Hospital, Beijing. NST patients were strictly matched 1:4 during the same period based on the TNM stage. Statistical comparisons were performed to determine the differences in survival between NST and NECB patients and to identify clinical factors that correlate with prognosis.ResultsA total of 121 participants affected by primary NECB were included in our analysis from November 2004 to November 2017. Elderly persons (>60 years of age) were more likely to have primary NECB than young persons (p=0.001). In addition, primary NECB patients had significantly higher odds of having tumors 2-5 cm (36.5%) and >5 cm (6.1%) in size than NST patients. Despite a significant difference in tumor size, the proportion of patients with lymph node metastases showed no difference between the two groups (p=0.021). In addition, the rate of patients with ER-negative tumors in the NECB group (4.2%) was significantly lower than that in the primary NST group (29.8%). Significant differences were noted in the PR-negative (13.3% versus 36.6%, P<0.001) and HER2-negative (90.5% versus 76.4%, P=0.001) expression statuses among these patients. Of 121 primary NECB patients, 11 (9.1%) experienced relapses during the follow-up period. We found that tumor size was an independent risk factor for relapse. For hormone receptors on tumor cells, ER-positive breast cancer patients had significantly lower odds of relapse than receptor-negative patients.ConclusionsOur data demonstrate no significant difference in mortality and relapse between the primary NECB and NST groups. The tumor size in the primary NECB group was significantly larger than that in the NST group. In addition, the absence of ER independently increased the relapse rate for breast carcinoma patients.

Impact of Transfer Learning Using Local Data on Performance of a Deep Learning Model for Screening Mammography.

"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To investigate the issues of generalizability and replication of deep learning (DL) models by assessing performance of a screening mammography DL system developed at New York University (NYU) on a local Australian dataset. Materials and Methods In this retrospective study, all individuals with biopsy and surgical pathology-proven lesions and age-matched controls were identified from a South Australian public mammography screening program (January 2010 to December 2016). The primary outcome was DL system performance, measured with the area under the receiver operating characteristic curve (AUC), in classifying invasive breast cancer or ductal carcinoma in situ (n = 425) from no malignancy (n = 490) or benign lesions (n = 44) in age-matched controls. The NYU system, including models without (NYU1) and with (NYU2) heatmaps, was tested in its original form, after training from scratch (without transfer learning; TL), after retraining with TL. Results The local test set comprised 959 individuals (mean age, 62.5 years [SD, 8.5]; all female). The original AUCs for the NYU1 and NYU2 models were 0.83 (95%CI = 0.82-0.84) and 0.89 (95%CI = 0.88-0.89), respectively. When applied in their original form to the local test set, the AUCs were 0.76 (95%CI = 0.73-0.79) and 0.84 (95%CI = 0.82-0.87), respectively. After local training without TL, the AUCs were 0.66 (95%CI = 0.62-0.69) and 0.86 (95%CI = 0.84-0.88). After retraining with TL, the AUCs were 0.82 (95%CI = 0.80-0.85) and 0.86 (95%CI = 0.84-0.88). Conclusion A deep learning system developed using a U.S. dataset showed reduced performance when applied 'out of the box' to an Australian dataset. Local retraining with transfer learning using available model weights improved model performance. ©RSNA, 2024.

Abstract PO2-13-08: Cell-free orphan noncoding RNAs and AI enable early detection of invasive breast cancer and ductal carcinoma in-situ

Abstract Background Earlier detection of breast cancer through mammography screening has reduced disease-specific mortality; however, confounding issues such as technical challenges, breast density, and tumor size can result in false negatives and ultimately later stage diagnosis. Next generation liquid biopsy has the potential to complement mammography and enable earlier detection for more women. We have previously demonstrated high sensitivity and specificity for early detection of invasive breast cancer (IBC) by utilizing a novel category of cancer-associated small RNAs, termed orphan noncoding RNAs (oncRNAs), through a liquid biopsy platform. Here, we further improve the ability to detect breast cancer in a larger, multi-source cohort through an AI-driven approach and demonstrate potential for detection of ductal carcinoma in-situ (DCIS). Methods We utilized The Cancer Genome Atlas (TCGA) small RNA-seq database to discover a library of 20,538 oncRNAs, through a female-specific analysis, that were significantly enriched among 1,103 breast tumors compared to 349 normal tissue samples spanning multiple tissue sites. The diagnostic performance of these oncRNAs were assessed in an independent cohort of archived serum samples from 663 female individuals, sourced from Indivumed (Hamburg, Germany), Proteogenex (Inglewood, CA), and MT Group (Los Angeles, CA), including 279 breast cancer patients of various stages (221 IBC and 58 DCIS; mean age: 57.0 ± 13.8 years; ever-smoker: 25.8%) and 304 age-matched controls (mean age: 58.5 ± 13.9 years; ever-smoker: 23.4%) without breast cancer. All samples were collected between 2010–2022 at time of diagnosis for breast cancer patients. We sequenced the small RNA content of these samples at an average depth of 25.28 ± 9.37 million 50-bp single-end reads. We detected 18,025 (87.8%) unique breast cancer-specific oncRNA species within at least one sample from the study cohort. We then trained a generative AI model using 5-fold cross-validation to predict cancer status for all samples. Results Our oncRNA-based model achieved an overall AUC of 0.95 (95% CI, 0.93–0.97) for prediction of IBC versus cancer-free controls with a sensitivity of 0.87 (0.82–0.91) at 90% specificity. We observed high sensitivities, also at 90% specificity, across all tumor stages and tumor sizes (Table 1). Sensitivities for the earliest stage and smallest tumor size were 0.87 (0.78–0.93) and 0.81 (0.61–0.93) for Stage I (n=83) and T1a–b ( >1mm to ≤10mm; n=26), respectively. Additionally, in a small single-source cohort, we also saw high model accuracy and sensitivity for DCIS, which we aim to confirm in additional cohorts. While our overall cancer cohort primarily consisted of individuals with luminal breast cancer, our model had high sensitivities across all breast cancer subtypes at 0.90 (0.84–0.94), 0.73 (0.59–0.85), and 0.86 (0.42–1.0) for luminal (n=181), HER2 positive (n=49), and triple negative (n=7), respectively. Conclusions We further demonstrate the potential utility of oncRNAs as a blood-based biomarker using an AI algorithm for sensitive and accurate early detection of breast cancer in a large cohort. Additionally, we have shown that this oncRNA-based assay performs well in detecting small, early-stage invasive breast tumors, with potential to detect precursors of breast cancer. Table 1: Model sensitivity in breast cancer by tumor stage and size For each tumor stage and size, as defined by the AJCC 7th Edition breast cancer staging system, sensitivity and 95% Pearson-Clopper confidence intervals (CI) are reported at 90% specificity for the number of samples (N). Citation Format: Noura Tbeileh, Taylor Cavazos, Mehran Karimzadeh, Jeffrey Wang, Alice Huang, Dung Ngoc Lam, Seda Kilinc, Jieyang Wang, Xuan Zhao, Andy Pohl, Helen Li, Lisa Fish, Kimberly Chau, Marra Francis, Lee Schwartzberg, Patrick Arensdorf, Hani Goodarzi, Fereydoun Hormozdiari, Babak Alipanahi. Cell-free orphan noncoding RNAs and AI enable early detection of invasive breast cancer and ductal carcinoma in-situ [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO2-13-08.

KDM7A-DT induces genotoxic stress, tumorigenesis, and progression of p53 missense mutation-associated invasive breast cancer

Stress-induced promoter-associated and antisense lncRNAs (si-paancRNAs) originate from a reservoir of oxidative stress (OS)-specific promoters via RNAPII pausing-mediated divergent antisense transcription. Several studies have shown that the KDM7A divergent transcript gene (KDM7A-DT), which encodes a si-paancRNA, is overexpressed in some cancer types. However, the mechanisms of this overexpression and its corresponding roles in oncogenesis and cancer progression are poorly understood. We found that KDM7A-DT expression is correlated with highly aggressive cancer types and specific inherently determined subtypes (such as ductal invasive breast carcinoma (BRCA) basal subtype). Its regulation is determined by missense TP53 mutations in a subtype-specific context. KDM7A-DT transcribes several intermediate-sized ncRNAs and a full-length transcript, exhibiting distinct expression and localization patterns. Overexpression of KDM7A-DT upregulates TP53 protein expression and H2AX phosphorylation in nonmalignant fibroblasts, while in semi-transformed fibroblasts, OS superinduces KDM7A-DT expression in a TP53-dependent manner. KDM7A-DT knockdown and gene expression profiling in TP53-missense mutated luminal A BRCA variant, where it is abundantly expressed, indicate its significant role in cancer pathways. Endogenous over-expression of KDM7A-DT inhibits DNA damage response/repair (DDR/R) via the TP53BP1-mediated pathway, reducing apoptosis and promoting G2/M checkpoint arrest. Higher KDM7A-DT expression in BRCA is associated with KDM7A-DT locus gain/amplification, higher histologic grade, aneuploidy, hypoxia, immune modulation scores, and activation of the c-myc pathway. Higher KDM7A-DT expression is associated with relatively poor survival outcomes in patients with luminal A or Basal subtypes. In contrast, it is associated with favorable outcomes in patients with HER2+ER- or luminal B subtypes. KDM7A-DT levels are coregulated with critical transcripts and proteins aberrantly expressed in BRCA, including those involved in DNA repair via non-homologous end joining and epithelial-to-mesenchymal transition pathway. In summary, KDM7A-DT and its si-lncRNA exhibit several intrinsic biological and clinical characteristics that suggest important roles in invasive BRCA and its subtypes. KDM7A-DT-defined mRNA and protein subnetworks offer resources for identifying clinically relevant RNA-based signatures and prospective targets for therapeutic intervention.

Abstract PO5-21-01: Carcinoma en cuirasse- a rare, but striking, cutaneous manifestation of metastatic breast cancer

Abstract Introduction: Carcinoma en cuirasse is a rare cutaneous metastatic presentation most commonly arising from primary breast cancers, typically after mastectomy. It appears like cellulitis and later develops into thickened rough patches of skin and even nodules. Carcinoma en cuirasse holds a poor prognosis, and treatment is difficult. Chemotherapeutic agents are unable to reach the tumor cells necessary, and radiation is ineffective because of skin curvature. Case Presentation: We report a female in her 70s with prior history of left breast ductal carcinoma in situ status post-radiation and lumpectomy, who presented with skin thickening of the left breast and solid masses in bilateral breasts 10 years later. Biopsy showed invasive ductal carcinoma of left breast (estrogen receptor [ER]/progesterone receptor positive [PR], human epidermal growth factor receptor-2 [HER2] negative) and ductal carcinoma in situ of right breast (ER/PR positive). She underwent right breast lumpectomy; however, the left breast mastectomy was aborted due to worsening of her skin findings on preoperative examination. An excisional skin biopsy revealed poorly differentiated invasive ductal carcinoma involving the dermis, deep dermis and focally involving the epidermis. Her diagnosis changed to stage 4 breast cancer, specifically carcinoma en cuirasse. Systemic treatment was initiated with palbociclib and letrozole and subsequently, she underwent left breast mastectomy given an excellent response to initial therapy. Surgical biopsy interestingly was HER2 positive and therefore her regimen was changed to taxotere, trastuzumab and pertuzumab. She completed adjuvant treatment and has been on maintenance trastuzumab along with letrozole currently and is doing well 5 years later with negative PET scans. Discussion: Our case is unique due to diagnosis of carcinoma en cuirasse before mastectomy, change in HER2 receptor status during treatment and excellent response to therapy with ongoing response to date. We think that an early diagnosis as well as targeted treatment could be the possible reasons for prolonged survival of more than 5 years. Conclusion: Any unexplained skin findings in breast cancer patients should prompt consideration of carcinoma en cuirasse. With ongoing treatment advances, many newer therapy options are available for metastatic breast cancer. Based on our case, we think that patients with this disease can have better outcomes. Citation Format: Manasi Godbole, Kashmira Wani, Shereen Zia, Vrushali Dabak. Carcinoma en cuirasse- a rare, but striking, cutaneous manifestation of metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-21-01.

Abstract PO3-20-10: Case Series: Invasive Secretory Carcinoma

Abstract Secretory variant invasive ductal carcinoma is not well described in the literature but is defined by its unique histopathology. These tumors stain positive for S100 and are typically triple negative hormonal cancers with an overall good prognosis. There is speculation that secretory carcinoma in adults is more aggressive with a greater likelihood for tumor recurrence. We present two case studies of this rare histopathologic diagnosis. First, a 76-year-old female with a recurrent secretory variant, invasive ductal carcinoma of the left breast. Second, a 68-year-old male who presented with invasive and in situ secretory carcinoma. A thorough chart review of all available institutional and outside institution records was performed from initial diagnosis to current treatment. Background information and de-identified patient information was summarized for this case series. This is a 76-year-old female who presented to her physician in 2011 with a palpable left breast and axillary mass. Her workup demonstrated ER+/PR+/HER2- invasive ductal carcinoma with lobular features of the left breast measuring 2.3 cm, along with a 1.5 cm malignant axillary lymph node. She underwent a left breast lumpectomy with axillary dissection. She underwent adjuvant whole breast radiation, axillary nodal radiation, and was placed on anastrozole therapy for 5 years. Seven years later a recurrence was noted in the superior aspect of the left breast. MRI guided biopsy revealed recurrent left breast cancer with pathology of invasive ductal carcinoma, secretory variant. She elected to undergo lumpectomy alone. Final pathology demonstrated invasive ductal carcinoma, secretory variant, ER negative (0%), PR negative (0%), HER2 negative (0%), pT1bNx. She underwent accelerated adjuvant partial breast radiation. Follow up and surveillance with bilateral breast MRI two years later demonstrated a new left breast mass, found to be triple negative, recurrent secretory variant invasive ductal carcinoma. She underwent definitive treatment with a left skin sparing mastectomy, right sentinel lymph node biopsy, and a latissimus dorsi flap with implant placement. Final pathology demonstrated multifocal recurrent secretory carcinoma, two foci measuring 6 and 11 mm. Our second patient was a 68-year-old male who initially presented to the clinic for evaluation of a ventral incisional hernia. During his initial assessment, a palpable retro-areolar nodule was noted on physical exam. Subsequent mammography demonstrated a hypoechoic mass with irregular margins measuring 2.8 x 2.3 x 1.7 cm along with increased vascularity and calcifications. An ultrasound guided biopsy demonstrated invasive secretory carcinoma. Initial pathologic testing of the tumor demonstrated ER positive (5%), PR positive (1%), and HER2 negative. The patient was taken to the operating room for a total mastectomy with sentinel lymph node biopsy. His postoperative pathology demonstrated negative margins, and invasive secretory carcinoma with lymph nodes negative for metastatic disease. Secretory variant of invasive ductal carcinoma is rare and is determined by its unique immunohistochemical features. We present two cases of secretory carcinoma at our institution. Data suggests that local recurrence is common in patients with secretory breast cancer, occurring in 33-44% of cases. Ki-67 index has been used as a prognostic indicator for metastases and recurrence of disease. Current treatment regimens are diverse; however, surgery is favored as the primary method. This report shows that although indolent, multifocality and recurrence is plausible. Given the limited data on this subset of carcinoma, more investigation is warranted to describe the effectiveness of adjuvant treatment options. Case 1 –insert figure image– Histopathologic examination at 200x shows invasive carcinoma with dense eosinophilic secretory material. By immunohistochemistry, the cells are negative for ER (0%) and PR (0%) with a HER2Neu score of 0, supporting the diagnosis of invasive secretory carcinoma. Case 2 –insert figure image– Histopathologic examination at 200x shows invasive carcinoma with dense eosinophilic secretory material. The tumor cells are positive for CK5/6 (patchy), CD117, ER (focal and weakly), and S100; negative for p63 and calponin, supporting the diagnosis of invasive secretory carcinoma. NTRK3 gene rearrangement was detected on fluorescence in situ hybridization (FISH). Citation Format: Lauren Geisel, Hemanth Venkatesh, Alyssa Obermiller, Quyen Chu, Jessica Gielow, Danielle Henry. Case Series: Invasive Secretory Carcinoma [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-20-10.

Acute adverse events of ultra-hypofractionated whole-breast irradiation after breast-conserving surgery for early breast cancer in Japan: an interim analysis of the multi-institutional phase II UPBEAT study.

The applicability of ultra-hypofractionated (ultra-HF) whole-breast irradiation (WBI) remains unknown in Japanese women. This study aimed to evaluate the safety and efficacy of this approach among Japanese women and report the results of an interim analysis performed to assess acute adverse events (AEs) and determine whether it was safe to continue this study. We enrolled Japanese women with invasive breast cancer or ductal carcinoma in situ who had undergone breast-conserving surgery, were aged ≥ 40years, had pathological stages of Tis-T3 N0-N1, and had negative surgical margins. Ultra-HF-WBI was delivered at 26Gy in five fractions over one week. When the number of enrolled patients reached 28, patient registration was paused for three months. The endpoint of the interim analysis was the proportion of acute AEs of grade ≥ 2 (Common Terminology Criteria for Adverse Events v5.0) within three months. Of the 28 patients enrolled from seven institutes, 26 received ultra-HF-WBI, and 2 were excluded due to postoperative infections. No AEs of grade ≥ 3 occurred. One patient (4%) experienced grade 2 radiation dermatitis, and 18 (69%) had grade 1 radiation dermatitis. The other acute grade 1 AEs experienced were skin hyperpigmentation (n = 10, 38%); breast pain (n = 4, 15%); superficial soft tissue fibrosis (n = 3, 12%); and fatigue (n = 1, 4%). No other acute AEs of grade ≥ 2 were detected. Acute AEs following ultra-HF-WBI were within acceptable limits among Japanese women, indicating that the continuation of the study was appropriate.

Abstract LB365: Generation of a novel severely immunodeficient Sprague Dawley rat model for xenograft studies

Abstract The recombinant-activating gene 2 (Rag2) plays a critical role in the recombination of the immunoglobulin and T cell receptor genes during the maturation of T and B cells. Loss of Rag2 protein leads to a lack of functional T and B cells, which eliminates the adaptive immune response. However, Rag2 deficiency alone may not guarantee the success of xenograft implantation, due to NK cells and other innate cells remaining. Il2rg is a key component of several cytokine receptors involved in differentiation and/or function of numerous adaptive and innate immune cells, including NK cells, mast cells, basophils, and dendritic cells. To generate a more severely immunodeficient rat model, both the Rag2 and Il2rg genes were knocked out in Sprague Dawley (SD) rats; this model was termed B-SDG rats. The immune profile and organ weights of thymus and spleen were investigated in B-SDG rats in comparison with Rag2-/- and wild-type SD rats. The spleen weights of both Rag2-/- and B-SDG rats were similar, but significantly reduced compared to wild-type SD rats. Notably, the thymus weights of B-SDG male rats were significantly smaller than those of Rag2-/- males. The immune cell profiles in thymus, spleen and blood were next evaluated by flow cytometry. A complete lack of B and T cells was observed in both Rag2-/- and B-SDG rats. B-SDG rats lacked CD161+ NK cells in the spleen and blood, which were maintained in Rag2-/- rats. Dendritic cells, monocytes, macrophages, and neutrophils were detected in all strains. In vivo xenograft implantation with human lung, bladder, breast, pancreas, acute monocytic and myelomonocytic leukemia tumor cell lines was next evaluated in B-SDG rats, which demonstrated successful engraftment. Furthermore, several efficacy studies were performed in B-SDG rats, including cisplatin chemotherapy on human breast invasive ductal carcinoma cell (HCC1954) and human large cell lung cancer cell (NCI-H460) xenografts, and a HER2-targeting ADC therapy was tested in B-SDG rats harboring human non-small cell lung cancer tumors (NCI-H1975). Taken together, these data confirm that B-SDG rats provide a powerful immunodeficient model for preclinical in vivo evaluation of novel drug candidates. Citation Format: Yanhui Nie, Meiqi Zhang, Wanling Zhong, Jia Feng, Bahetiyaer Huwatibieke, Zhaoxue Yu. Generation of a novel severely immunodeficient Sprague Dawley rat model for xenograft studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB365.

Development and validation of survival nomograms in elder triple-negative invasive ductal breast carcinoma patients

ABSTRACT Background We aimed to develop a nomogram to predict the overall survival of elderly patients with Triple-negative invasive ductal breast carcinoma (TNIDC). Research design and methods 12165 elderly patients with nonmetastatic TNIDC were retrieved from the SEER database from 2010 to 2019 and were randomly assigned to training and validation cohorts. Stepwise Cox regression analysis was used to select variables for the nomogram based on the training cohort. Univariate and multivariate Cox analyses were used to calculate the correlation between variables and prognosis of the patients. Survival analysis was performed for high- and low-risk subgroups based on risk score. Results Eleven predictive factors were identified to construct our nomograms. Compared with the TNM stage, the discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.741 (95% CI 0.728–0.754) against 0.708 (95% CI 0.694–0.721) and 0.765 (95% CI 0.747–0.783) against 0.725 (95% CI 0.705–0.744) for the training and validation cohorts, respectively. Differences in OS were also observed between the high- and low-risk groups (p < 0.001). Conclusion The proposed nomogram provides a convenient and reliable tool for individual evaluations for elderly patients with M0_stage TNIDC. However, the model may only for Americans.

Increase in Hypofractionated Radiation Therapy Among Patients with Invasive Breast Cancer or Ductal Carcinoma In Situ: Who is Left Behind?

We aimed to update the trend of hypofractionated whole-breast irradiation (HF-WBI) use over time in the US and examine factors associated with lack of HF-WBI adoption for patients with early-stage invasive breast cancer (IBC) or ductal carcinoma in situ (DCIS) undergoing a lumpectomy. Among patients who underwent a lumpectomy, we identified 928,034 early-stage IBC patients and 330,964 DCIS patients in the 2004-2020 National Cancer Database. We defined HF-WBI as 2.5-3.33 Gy/fraction to the breast and conventional fractionated whole-breast irradiation as 1.8-2.0 Gy/fraction. We evaluated the trend of HF-WBI utilization using a generalized linear model with the log link and binomial distribution. Factors associated with HF-WBI utilization were assessed using multivariable logistic regression in patients diagnosed between 2018 and 2020. Among IBC patients, HF-WBI use has significantly increased from 0.7% in 2004 to 63.9% in 2020. Similarly, HF-WBI usage among DCIS patients has also increased significantly from 0.4% in 2004 to 56.6% in 2020. Black IBC patients were less likely than White patients to receive HF-WBI (adjusted odds ratio [AOR] 0.81, 95% CI: 0.77-0.85). Community cancer programs were less likely to administer HF-WBI to IBC patients (AOR 0.80, 95% CI: 0.77-0.84) and to those with DCIS (AOR 0.87, 95% CI: 0.79-0.96) than academic/research programs. Younger age, positive nodes, larger tumor size, low volume programs, and facility location were also associated with lack of HF-WBI adoption in both patient cohorts. HF-WBI utilization among post-lumpectomy patients has significantly increased from 2004-2020 and can finally be considered standard of care in the US. We found substantial disparities in adoption within patient and facility subgroups. Reducing disparities in HF-WBI adoption has the potential to further alleviate healthcare costs while improving patients' quality of life.

A tricky singular papular peri‐cicatricial mammarian lesion

AbstractBreast cancer represents the most common malignancy in women worldwide. In most cases, metastasis is the leading cause of mortality. Early diagnosis is still challenging despite standardised, government‐led screening programs, but is crucial in achieving improved survival rates. Additionally, a deeper understanding of the metastatic potential of breast cancer is critical for developing therapeutic interventions to combat widespread disease. Cutaneous metastasis from underlying breast carcinoma is uncommon as the first manifestation of visceral malignancies and is commonly observed in advanced‐stage malignancies, often associated with poor prognosis, and a prompt, precise tissue diagnosis is mandatory. A high index of suspicion in oncologic patients is required to diagnose these lesions, as they can mimic benign skin manifestations and clinical findings may be subtle and going unnoticed. We report on a case of a 76‐year‐old female patient presenting to our non‐invasive diagnostic outpatient clinic with an unusual cutaneous presentation, as an early sign of locally advanced invasive ductal carcinoma breast cancer recurrence. The aim of our article is to underline the importance of the dermatologist in the multi‐disciplinary oncologic diagnostic process, including non‐invasive imaging evaluation of cutaneous lesions, especially insidious breast carcinomas. Dynamic optical coherence tomography (D‐OCT) is not routinely used due to its cost, therefore lesion's aspect has not been completely described, consequently, the correct evaluation of skin architecture appearance can add important information, especially in cutaneous oncology where it can help in early diagnosis or cancer recurrency. OCT may contribute to the detection of subclinical cutaneous manifestations of cancer or recurrence, in particular, when they are difficult to differentiate clinically from benign lesion. In the case we described, OCT of suspected lesion showed the loss of the DEJ with solid nests and irregular vessels.

DEBCM: Deep Learning-Based Enhanced Breast Invasive Ductal Carcinoma Classification Model in IoMT Healthcare Systems.

Accurate breast cancer (BC) diagnosis is a difficult task that is critical for the proper treatment of BC in IoMT (Internet of Medical Things) healthcare systems. This paper proposes a convolutional neural network (CNN)-based diagnosis method for detecting early-stage breast cancer. In developing the proposed method, we incorporated the CNN model for the invasive ductal carcinoma (IDC) classification using breast histology image data. We have incorporated transfer learning (TL) and data augmentation (DA) mechanisms to improve the CNN model's predictive outcomes. For the fine-tuning process, the CNN model was trained with breast histology image data. Furthermore, the held-out cross-validation method for best model selection and hyper-parameter tuning was incorporated. In addition, various performance evaluation metrics for model performance assessment were computed. The experimental results confirmed that the proposed model outperformed the baseline models across all evaluation metrics, achieving 99.04% accuracy. We recommend the proposed method for early recognition of BC in IoMT healthcare systems due to its high performance.

Case Report: Contribution of [18F]FET PET in differential diagnosis between radionecrosis and progression in metastasis—reproducibility and superiority of dynamic acquisitions

We present the case of a 67-year-old woman with metastatic invasive ductal carcinoma of the left breast, in whom a follow-up magnetic resonance imaging, 3 months after encephalic radiotherapy, revealed a significant increase in the size of two brain metastases, potentially indicating progressive disease within the radiation field. Subsequent [18F] fluorodeoxyglucose ([18F]FDG) and [18F] fluoroethyl-L-tyrosine positron emission tomography ([18F]FET PET) scans were performed to distinguish radionecrosis from tumor progression. Despite a dynamic [18F]FET time–activity curve (TAC) against progression, the exceeding of the 1.9 cutoff by mean tumor to brain ratio (TBR) and interdisciplinary considerations led to the resection of one lesion. Histopathology revealed necrosis due to radiotherapy, without viable tumor proliferation. To verify radionecrosis, a second [18F]FET PET scan was conducted, showing consistent findings. In metastasis differentiation, the mean TBR cutoff of 1.9 and TAC analysis achieved a sensitivity of 95% and specificity of 91%. The discrepancy between the TAC and TBR emphasizes the need for consideration, and a time delay between radiotherapy and PET may impact TBR cutoffs. In addition, differences in radiosensitivity suggest a lower metastasis pre-test probability of progression, and it might be why a TAC analysis could be more effective in distinguishing true progression from treatment related changes in metastasis. This case demonstrates the accuracy of dynamic [18F]FET PET and suggests its utility for post-treatment metastasis evaluation, and further research on post-treatment delay could lead to improved performances of dynamic [18F]FET PET.

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

BackgroundAlthough lung and breast cancers are common malignancies, the occurrence of primary synchronous neoplasms involving these organs has been rarely reported in literature.Case presentationA 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).ConclusionsTo 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.

Primary fallopian tube cancer followed by primary breast cancer in RAD51C mutation carrier treated with niraparib as first line maintenance therapy: a case report

Given the rarity of RAD51C mutations, the risk and treatment of metachronous breast cancer after the diagnosis of ovarian cancer in RAD51C mutation carriers is not clear, especially for those who have received PARPi treatment. We report the case of a 65-year-old woman diagnosed with stage IIIC high-grade serous primary fallopian tube cancer. The patient had no family history of breast or ovarian cancer. The patient received three cycles of neoadjuvant chemotherapy with paclitaxel and carboplatin and achieved a complete response. After interval debulking surgery, the patient received three cycles of adjuvant chemotherapy. Collection and extraction of saliva DNA for next-generation sequencing identified a RAD51C mutation c.838-2 A > G. The patient received niraparib as front-line maintenance treatment. After 36 months of niraparib treatment, the patient had grade II invasive ductal carcinoma of the left breast that was positive for estrogen receptor (90%) and Ki-67 (30%) and negative for progesterone receptor and human epidermal growth factor receptor 2. Computed tomography revealed the absence of distant metastases. Modified radical mastectomy and axillary lymph node dissection were then performed. The final pathological report of the breast showed a 1.8 cm Bloom-Richardson grade II invasive ductal carcinoma in the left breast with axillary lymph node metastasis (1/21). Finally, the breast cancer was stage IIA, pT1cN1M0. The metachronous breast cancer in this case may be the first report of second primary cancer in fallopian tube cancer patient harboring a RAD51C mutation during niraparib treatment. Further studies are required to determine optimal treatment.

Breast cancer characteristics in elderly women: A comprehensive cohort study of 7,965 patients

Purpose Breast cancer in older women is a major public health issue as there is an age-related excess mortality. Our aim was to study the tumor characteristics at diagnosis, treatment and outcomes in order to identify possible ways of improving breast cancer management in elderly women.Methods We conducted a single-institution retrospective analysis on a cohort of 7,965 women with invasive breast cancer or Ductal Carcinoma in situ (DCIS) who were treated between 2001 and 2017. This cohort was constituted with a machine learning-based tool called SENOMETRY (NCT02810093) which allowed us to extract structured data from unstructured Electronic Health Records. Patients were divided in 3 groups according to the age at diagnosis: younger (< 49, N = 2001), middle-aged (50 to 74, N = 4859) and elderly (≥ 75, N = 1105).Results In elderly women breast cancer had more favorable predictive factors (more estrogen receptors P < 0.001, less Human Epidermal growth-factor Receptor 2 overexpression P = 0.009) and prognostic factors (less Ki67 > 30 %, P = 0.001) factors. Tumors were diagnosed at a more advanced local stage (P < 0.001). Lymph node involvement decreased before 70 (ρ -0.033, P = 0.027) and increased again after this threshold (ρ +0.065, P = 0.021). Older women underwent heavier surgical procedures (P < 0.001 to 0.049) and more surgical abstention (P < 0.001) for invasive carcinomas while no difference was noted for patients with DCIS only (P ranged from 0.280 to 0.440). Older women had less chemotherapy (P < 0.001). Elderly women had higher overall mortality and lower locoregional recurrence (P < 0.001). Specific mortality increased with age after 75 (P = 0.042). No difference of relapse-free or overall survival was noted for axillary lymph node dissection compared to sentinel lymph node biopsy in elderly women, after adjustement on tumor size and lymph node involvement.Conclusion Our findings suggest that axillary surgery de-escalation and earlier diagnosis would be and accessible way of improving breast cancer management in older women.

Are better AI algorithms for breast cancer detection also better at predicting risk? A paired case–control study

BackgroundThere is increasing evidence that artificial intelligence (AI) breast cancer risk evaluation tools using digital mammograms are highly informative for 1–6 years following a negative screening examination. We hypothesized that algorithms that have previously been shown to work well for cancer detection will also work well for risk assessment and that performance of algorithms for detection and risk assessment is correlated.MethodsTo evaluate our hypothesis, we designed a case-control study using paired mammograms at diagnosis and at the previous screening visit. The study included n = 3386 women from the OPTIMAM registry, that includes mammograms from women diagnosed with breast cancer in the English breast screening program 2010–2019. Cases were diagnosed with invasive breast cancer or ductal carcinoma in situ at screening and were selected if they had a mammogram available at the screening examination that led to detection, and a paired mammogram at their previous screening visit 3y prior to detection when no cancer was detected. Controls without cancer were matched 1:1 to cases based on age (year), screening site, and mammography machine type. Risk assessment was conducted using a deep-learning model designed for breast cancer risk assessment (Mirai), and three open-source deep-learning algorithms designed for breast cancer detection. Discrimination was assessed using a matched area under the curve (AUC) statistic.ResultsOverall performance using the paired mammograms followed the same order by algorithm for risk assessment (AUC range 0.59–0.67) and detection (AUC 0.81–0.89), with Mirai performing best for both. There was also a correlation in performance for risk and detection within algorithms by cancer size, with much greater accuracy for large cancers (30 mm+, detection AUC: 0.88–0.92; risk AUC: 0.64–0.74) than smaller cancers (0 to < 10 mm, detection AUC: 0.73–0.86, risk AUC: 0.54–0.64). Mirai was relatively strong for risk assessment of smaller cancers (0 to < 10 mm, risk, Mirai AUC: 0.64 (95% CI 0.57 to 0.70); other algorithms AUC 0.54–0.56).ConclusionsImprovements in risk assessment could stem from enhancing cancer detection capabilities of smaller cancers. Other state-of-the-art AI detection algorithms with high performance for smaller cancers might achieve relatively high performance for risk assessment.

MicroRNA signatures differentiate types, grades, and stages of breast invasive ductal carcinoma (IDC): miRNA-target interacting signaling pathways

BackgroundInvasive ductal carcinoma (IDC) is the most common form of breast cancer which accounts for 85% of all breast cancer diagnoses. Non-invasive and early stages have a better prognosis than late-stage invasive cancer that has spread to lymph nodes. The involvement of microRNAs (miRNAs) in the initiation and progression of breast cancer holds great promise for the development of molecular tools for early diagnosis and prognosis. Therefore, developing a cost effective, quick and robust early detection protocol using miRNAs for breast cancer diagnosis is an imminent need that could strengthen the health care system to tackle this disease around the world.MethodsWe have analyzed putative miRNAs signatures in 100 breast cancer samples using two independent high fidelity array systems. Unique and common miRNA signatures from both array systems were validated using stringent double-blind individual TaqMan assays and their expression pattern was confirmed with tissue microarrays and northern analysis. In silico analysis were carried out to find miRNA targets and were validated with q-PCR and immunoblotting. In addition, functional validation using antibody arrays was also carried out to confirm the oncotargets and their networking in different pathways. Similar profiling was carried out in Brca2/p53 double knock out mice models using rodent miRNA microarrays that revealed common signatures with human arrays which could be used for future in vivo functional validation.ResultsExpression profile revealed 85% downregulated and 15% upregulated microRNAs in the patient samples of IDC. Among them, 439 miRNAs were associated with breast cancer, out of which 107 miRNAs qualified to be potential biomarkers for the stratification of different types, grades and stages of IDC after stringent validation. Functional validation of their putative targets revealed extensive miRNA network in different oncogenic pathways thus contributing to epithelial-mesenchymal transition (EMT) and cellular plasticity.ConclusionThis study revealed potential biomarkers for the robust classification as well as rapid, cost effective and early detection of IDC of breast cancer. It not only confirmed the role of these miRNAs in cancer development but also revealed the oncogenic pathways involved in different progressive grades and stages thus suggesting a role in EMT and cellular plasticity during breast tumorigenesis per se and IDC in particular. Thus, our findings have provided newer insights into the miRNA signatures for the classification and early detection of IDC.

Abstract B042: Analysis of predictive indicators of invasive breast cancer: Modeling survival rates

Abstract Objective: We aim to investigate indicators of risk for invasive breast cancer (IBC) and to predict and assess the impact of these risk indicators on survival rates in breast cancer (BC) patients who received various therapies. Background: It has been identified that several indicators including BC subtypes, age at diagnosis, history of breast disease, menopausal status, estrogen receptor (ER) status, progesterone receptor (PR) status, human epidermal growth receptor (HER2) status, tumor stage, tumor size, among others, can cause genomic alterations and driver mutations in BC, leading to invasive carcinogenesis. To assure improved BC outcomes, we investigate the influence of BC indicators on survival rates in patients receiving hormone therapy, chemotherapy and radiotherapy. Methods: This study uses the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset, which included 31 clinical indicators, m-RNA levels z-score for 331 genes, and mutation in 175 genes for 1904 BC patients. Both bivariate and multivariate associations were examined using logistic regression and Cox proportional hazard models. The multivariate logistic regression analysis is used to determine predictors of IBC. The Cox proportional hazard model was also used to evaluate the magnitude of the impacts of clinical and demographic variables on IBC, as well as the effects of therapy on survival. All analyses for this investigation were carried out using SAS. A p-value &amp;lt; 0.05 was considered statistically significant. Results: We examined 1,043 patients (with the median age 61±13.1 years) from a total of 1904 for this study: 78.8% of patients had breast invasive ductal carcinoma; 87.4% were HER2 negative; 22.8%, 60.7%, and 67.6% received chemotherapy, hormone therapy, and radiotherapy treatments, respectively; 56.9% died but only 34.6% died from the disease; the average overall survival months was 127.3±77.6 months; and the most common age group was "65+ years" (39.4%). Chemotherapy (p=0.0474), neoplasm histologic grade (p=0.0015), Nottingham prognostic index (p&amp;lt;.0001), radiation (p=0.0068), and BReast CAncer gene 1 (BRCA1) (p=0.0251) were all associated with IBC. Overall survival was also correlated to age at diagnosis (p=0.0002), neoplasm histologic grade (p&amp;lt;.0001), lymph nodes (p&amp;lt;.0001), mutation count (p&amp;lt;.0001), Nottingham prognostic index (p&amp;lt;.0001), radiotherapy (p=0005), tumor size (p&amp;lt;.0001), tumor stage (p&amp;lt;.0001), BRCA1 (p=0.250), PTEN (p&amp;lt;.0001), and TP53 (p=0.0248). The overall accuracy of the model for each IBC and survival status was 82.1% and 74.2%, respectively. Conclusion: Our analysis demonstrated the importance of predictive analysis using the logistic regression model and survival analysis using the Cox proportional hazard model in cancer research. Predictive and survival analysis results aided in predicting the invasiveness and survival rate of BC among the study participants. In general, predictive and survival analyses are more accurate and may be used to make more realistic treatment decisions and precision oncology. Citation Format: Olumide Arigbede, Gebre-Egziabhe Kiros. Analysis of predictive indicators of invasive breast cancer: Modeling survival rates [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr B042.