Pleomorphic Carcinoma Research Articles

Exploration of cancer associated fibroblasts phenotypes in the tumor microenvironment of classical and pleomorphic Invasive Lobular Carcinoma.

Multiplex immunofluorescence were performed on formalin fixed paraffin embedded tissues using Opal-7 color kit. The antibodies used for phenotyping CAFs were Pan CK (AE1/AE3), CD45, A-SMA, FAP, S100, Thy-1 with optimized dilutions. The images were acquired and analyzed using Vectra 3.0 imaging system and InForm software respectively. We studied 19 different CAFs colocalized phenotypes in the tumor, stroma and overall tissue compartments between classic and pleomorphic ILC. Total A-SMA+, A-SMA+FAP+S100+ and A-SMA+S100+ CAFs demonstrated higher densities in classic ILC cases while FAP+S100+ and S-100+ CAFs were increased in the pleomorphic subtype samples. Our study explores multiple CAFs phenotypes between classical and pleomorphic ILC. We showed that CAFs subset differ between Classic ILC and Pleomorphic ILC. A-SMA CAFs are more prevalent in the TME of classic ILCs whereas Pleomorphic ILCs are dominated by CAFs without A-SMA expression. This also iterates the importance of exploring this particular type of breast carcinoma in more detail, paving the way for meaningful translational research.

Lobular Neoplasia Diagnosed by MRI-Guided Breast Biopsy: Identifying Upgrade Rate to Malignancy and Outcomes of Clinical and Surgical Management.

The aim of this study was to determine surgical and clinical outcomes of lobular neoplasia (LN) diagnosed by magnetic resonance imaging (MRI) biopsy, including upgrade to malignancy, and to assess for characteristics associated with upgrade. A single-institution retrospective study, between 2013 and 2022, of patients with histopathological findings of LN via MRI-guided biopsy was performed using an institutional database and review of the electronic medical records. Decision for excision or surveillance was made by a multidisciplinary team per institutional practice. Patient demographics and imaging characteristics were summarized using descriptive analyses. Upgrade was defined as upgrade to cancer on surgical pathology for patients treated with excision or the development of cancer at the biopsy site during surveillance. The Wilcoxon rank-sum test and Fisher's exact test were used to compare features of the upgraded cohort with the remainder of the group. Ninety-four MRI biopsies diagnosing LN were included. Median age was 57 years (range 37-78years). Forty-six lesions underwent excision while 48 lesions were surveilled. The upgrade rate was 7.4% (7/94). Upgrades in the excised cohort consisted of pleomorphic lobular carcinoma in situ (LCIS; n=1), ductal carcinoma in situ (DCIS; n=3) and invasive lobular carcinoma (ILC; n=2), while one interval development of DCIS was observed at the site of biopsy in the surveillance cohort. No MRI or patient variables were associated with upgrade. In this contemporary cohort of MRI-detected LNs, the upgrade rate was low. Omission of surgery for MRI-detected LNs in carefully selected patients may be considered in a shared decision-making capacity between the patient and the treatment team. Larger cohorts are needed to determine factors predictive of upgrade risk.

Influence of p16 Protein Immunostaining on Histopathological Features of Pleomorphic Adenoma and Carcinoma ex- Pleomorphic Adenoma.

The objective of this study was to evaluate the role of p16 in histologic characteristics and transition of Pleomorphic Adenoma (PA) to Carcinoma ex-PA (CxPA). So, 60 PA and 4 CxPA were histologic reviewed based on microscopic characteristics proposed by Hellquist, Triantafyllou and Dulguerov (PA) and Morais, Antony and Toluie (CxPA). Immunostaining for p16 was associated in different parenchyma and stroma of both tumors and Fisher's/chi-square tests and Mann-Whitney test were performed (SPSS v20.0, p<0.05). In PA the periductal cells were predominantly p16- and that ductal and myoepithelial cells showed a significant increase in p16+ cells (p<0.001). In CxPA, none of the cases showed p16+ in periductal cells, most parotid cases showed p16+ in ductal cells, and one case of parotid and the submandibular case showed mild immunostaining for myoepithelial cells. There was a small reduction in p16+ in CxPA compared to PA (p=0.537), but in both tumors there was less p16+ cells in solid stroma than other (p<0.001). The p16+ cases of PA had a higher capsular thickness (p=0.047). So, the loss of p16 immunostaining does not seem to be associated with the transition from PA to CxPA, but in both tumors the loss of p16+ cells are related to microscopic aggressiveness.

EP06.05-15 STAS and Expression of EMT-markers in Surgically Resected Lung Pleomorphic Carcinomas

EP06.05-15 STAS and Expression of EMT-markers in Surgically Resected Lung Pleomorphic Carcinomas

EP06.05-11 Immunohistochemical Features in Tissue Microarray in Pleomorphic Carcinoma of the Lungs

EP06.05-11 Immunohistochemical Features in Tissue Microarray in Pleomorphic Carcinoma of the Lungs

P1.21-21 PD-L1 Expression in Surgically Resected Lung Pleomorphic Carcinoma - One-centre Study of 107 Patients

P1.21-21 PD-L1 Expression in Surgically Resected Lung Pleomorphic Carcinoma - One-centre Study of 107 Patients

EP07.01-03 Perioperative Outcomes & Strategies for Pleomorphic Carcinoma in Lung

EP07.01-03 Perioperative Outcomes & Strategies for Pleomorphic Carcinoma in Lung

Clinicopathological features and differential diagnosis of gastric pleomorphic giant cell carcinoma.

The aim of this study was to investigate the clinicopathological features and differential diagnosis of gastric pleomorphic giant cell carcinoma. Histopathology, immunohistochemistry, and human epidermal growth factor receptor 2 (HER2) gene testing were conducted for seven cases of gastric pleomorphic giant cell carcinoma. In histomorphological terms, all seven cases involved pleomorphic giant cell carcinoma, accounting for more than 10% of the entire tumor, with pleomorphic spindle cells and giant cells mixed with various histomorphological structures of adenocarcinoma with high, intermediate, and low differentiation. There was large heterogeneity in the HER2 protein expression and HER2 gene amplification in the gastric pleomorphic giant cell carcinoma, and both levels of HER2 were focal in three cases, accounting for 42.9% (3/7). The mismatch repair gene proteins MLH1, MSH2, PMS2, and MSH6 were positive. Routine immunohistochemical markers, i.e., pan-cytokeratin, epithelial membrane antigen, villin, caudal-type homeobox 2, E-cadherin, and p53, were positive in the gastric pleomorphic giant cell carcinoma, while vimentin, calponin, smooth muscle actin, nestin, S-100, cluster of differentiation (CD) 99, desmin, and CD34 were focally expressed in both the spindle and the giant cells, with Ki-67-positive cells accounting for 70-80%. Gastric pleomorphic giant cell carcinoma presents multiple histomorphological features and is easily confused with various tumors. Clarifying the histopathological features of this type of tumor is important for differential diagnosis and precise treatment.

Genomic Analysis in the Categorization of Poorly Differentiated Primary Liver Carcinomas.

A subset of primary liver carcinomas (PLCs) cannot be classified as hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (iCCA) based on morphology and immunohistochemistry (IHC). This includes tumors with morphology suggestive of HCC but lacking hepatocellular marker expression, tumors with ambiguous morphology characterized by co-expression of hepatocellular and cholangiocytic markers, and undifferentiated pleomorphic carcinomas with no discernible line of differentiation on morphology or IHC. This study examines the role of genomic analysis in the categorization of these tumors. Genomic analysis was performed on 16 PLCs that could not be definitely classified as HCC or iCCA based on morphology and IHC using a capture-based next-generation sequencing assay (n=15) or single gene mutational analysis (n=1). Genomic alterations in TERT promoter were seen in 9/16 cases (56%) and strongly favored HCC. Genomic alterations favoring iCCA were seen in 5/16 cases (31%) and included mutations in IDH1 , PBRM1 , BAP1 , and ERBB2 , as well as FGFR2 fusion. Genomic changes were helpful in classifying 14/16 (87%) PLCs. Though not specific, these genomic alterations can provide valuable diagnostic clues in selected morphologically and immunohistochemically unclassifiable cases. Given the important differences in management between HCC and iCCA, routine use of genomic analysis in diagnostically challenging settings should be considered.

Pulmonary Pleomorphic Carcinoma: Its Clinical Behavior, Prognostic Factor, and Keys to Treatment

Pulmonary Pleomorphic Carcinoma: Its Clinical Behavior, Prognostic Factor, and Keys to Treatment

Adding automated decision-tree models to multiparametric MRI for parotid tumours improves clinical performance

PurposeTherapeutic management of parotid gland tumours depends on their histological type. To aid its characterisation, we sought to develop automated decision-tree models based on multiparametric magnetic resonance imaging (MRI) parameters and to evaluate their added diagnostic value compared with morphological sequences. Methods206 MRIs from 206 patients with histologically proven parotid gland tumours were included from January 2009 to January 2018. Multiparametric MRI findings (including parameters derived from diffusion-weighted imaging [DWI] and dynamic contrast-enhanced [DCE]) were used to build predictive classification and regression tree (CART) models for each histological type. All MRIs were read twice: first, based on morphological sequence findings only, and second, with the addition of multiparametric sequences and CART findings. The diagnostic performance between these two readings was compared using ROC curves. ResultsCompared to morphological sequences alone, the addition of multiparametric analysis significantly increased the diagnostic performance for all histological types (p < 0.001 to p = 0.011), except for lymphomas, where the increase was not significant (AUC 1.00 vs. 0.99, p = 0.066). ADCmean was the best parameter to identify pleomorphic adenomas, carcinomas and lymphomas with respective cut-offs of 1.292 × 10–3 mm2/s, 1.181 × 10–3 mm2/s and 0.611 × 10–3 mm2/s, respectively. × 10–3 mm2/s. The mean extracellular-extravascular space coefficient was the best parameter to Warthin tumours from the others, with a cut-off of 0.07. ConclusionsThe addition of decision tree prediction models based on multiparametric sequences improves the non-invasive diagnostic performance of parotid gland tumours. ADC and extracellular-extravascular space coefficient are the two best parameters for decision making.

Primary Mucinous Cystadenocarcinoma of the Breast Intermixed with Pleomorphic Invasive Lobular Carcinoma: The First Report of This Rare Association.

Primary mucinous cystadenocarcinoma (MCA) is a rare breast carcinoma subtype showing overlapping histopathological features with mucinous cystadenocarcinoma of the ovary and pancreas. Current literature data suggest a favorable prognosis of breast MCAs despite its immunoprofile usually revealing lack of expression of estrogen receptor, progesterone receptor and HER-2 and high Ki67. As far as we know, only 36 cases have been reported in the literature to date. Its ambiguous morpho-phenotypic profile makes histological diagnosis very challenging. It must be distinguished from typical mucin-producing breast carcinomas and, above all, metastases from the same histotype in other sites (ovary, pancreas, appendix). Herein, we report the case of a primary breast MCA occurring in a 41-year-old female with peculiar histological features.

Tumor-Infiltrating Lymphocytes and PD-L1 Expression in Pleomorphic Lobular Breast Carcinoma.

The prognostic and predictive role of stromal tumor-infiltrating lymphocytes (sTILs) is undetermined in pleomorphic invasive lobular cancer (pILC). The same applies for the expression of PD-1/PD-L1 in this rare breast cancer subtype. Here, we aimed to investigate the expression of sTILs and analyze the PD-L1 expression levels in pILC. Archival tissues from sixty-six patients with pILC were collected. The sTIL density was scored as a percentage of tumor area using the following cut-offs: 0%; <5%; 5-9%; and 10-50%. The PD-L1 expression was analyzed using IHC on formalin-fixed, paraffin-embedded tissue sections using SP142 and 22C3 antibodies. A total of 82% of the sixty-six patients were hormone receptor positive and 8% of cases were triple negative (TN), while 10% showed human epidermal growth factor receptor 2 (HER2) amplification. sTILs (≥1%) were present in 64% of the study population. Using the SP142 antibody, 36% of tumors demonstrated a positive PD-L1 score of ≥1%, and using the 22C3 antibody, 28% had a positive PD-L1 score of ≥1. There was no correlation between sTILs or PD-L1 expression and tumor size, tumor grade, nodal status, expression of estrogen receptor (ER), or amplification of HER2. Our data did not show any difference in survival between the three molecular subtypes of pILC with respect to sTILs and PD-L1 expression. This study shows that pILCs show some degree of sTILs and PD-L1 expression; however, this was not associated with a survival improvement. Additional large trials are needed to understand immune infiltration in lobular cancer, especially in the pleomorphic subtype.

Establishment, characterization, and drug screening of low-passage patient individual non-small cell lung cancer in vitro models including the rare pleomorphic subentity.

For pre-clinical drug development and precision oncology research, robust cancer cell models are essential. Patient-derived models in low passages retain more genetic and phenotypic characteristics of their original tumors than conventional cancer cell lines. Subentity, individual genetics, and heterogeneity greatly influence drug sensitivity and clinical outcome. Here, we report on the establishment and characterization of three patient-derived cell lines (PDCs) of different subentities of non-small cell lung cancer (NSCLC): adeno-, squamous cell, and pleomorphic carcinoma. The in-depth characterization of our PDCs included phenotype, proliferation, surface protein expression, invasion, and migration behavior as well as whole-exome and RNA sequencing. Additionally, in vitro drug sensitivity towards standard-of-care chemotherapeutic regimens was evaluated. The pathological and molecular properties of the patients' tumors were preserved in the PDC models HROLu22, HROLu55, and HROBML01. All cell lines expressed HLA I, while none were positive for HLA II. The epithelial cell marker CD326 and the lung tumor markers CCDC59, LYPD3, and DSG3 were also detected. The most frequently mutated genes included TP53, MXRA5, MUC16, and MUC19. Among the most overexpressed genes in tumor cells compared to normal tissue were the transcription factors HOXB9, SIM2, ZIC5, SP8, TFAP2A, FOXE1, HOXB13, and SALL4; the cancer testis antigen CT83; and the cytokine IL23A. The most downregulated genes on the RNA level encode the long non-coding RNA LANCL1-AS1, LINC00670, BANCR, and LOC100652999; the regulator of angiogenesis ANGPT4; the signaling molecules PLA2G1B and RS1; and the immune modulator SFTPD. Furthermore, neither pre-existing therapy resistances nor drug antagonistic effects could be observed. In summary, we successfully established three novel NSCLC PDC models from an adeno-, a squamous cell, and a pleomorphic carcinoma. Of note, NSCLC cell models of the pleomorphic subentity are very rare. The detailed characterization including molecular, morphological, and drug-sensitivity profiling makes these models valuable pre-clinical tools for drug development applications and research on precision cancer therapy. The pleomorphic model additionally enables research on a functional and cell-based level of this rare NCSLC subentity.

Clinical outcomes following total en bloc spondylectomy for spinal metastases from lung cancer

BackgroundThe current guidelines for the treatment of non-small cell lung cancer encourage local curative treatment for selected patients with oligometastases. This study evaluated the surgical results of total en bloc spondylectomy (TES) for isolated spinal metastases originating from lung cancer in carefully selected patients. MethodsWe retrospectively reviewed 14 patients (7 men and 7 women) who underwent TES for spinal metastases originating from lung cancer between 2000 and 2017. The primary outcome measure was the postoperative overall survival time. The histological types included adenocarcinoma (n = 12), pleomorphic carcinoma (n = 1), and small cell lung carcinoma (SCLC) (n = 1 patient). We assessed postoperative survival using Kaplan–Meier analysis and the log-rank test. ResultsThe median postoperative survival time was 83.0 months (6–162 months) in 13 patients with non-small cell lung carcinoma (NSCLC) and 6 months in 1 patient with SCLC. The 3-, 5-, and 10-year overall survival rates in patients with NSCLC were 61.5%, 53.8%, and 15.4%, respectively. Poor postoperative performance status (PS) and Frankel grade, and preoperative irradiation to the vertebrae to be resected were significantly associated with short-term survival after TES in patients with NSCLC (p < 0.05). ConclusionsThe surgical results of TES for spinal metastases of lung cancer were relatively favorable among carefully selected patients. TES may be indicated for spinal metastases of lung cancer in patients with controlled primary lung cancer, NSCLC histology, prospect of good postoperative PS, and preferably no irradiation to the target vertebrae.

ROLE OF SEROUS FLUID CYTOLOGY IN BOTH NON-MALIGNANT AND MALIGNANT LESIONS WITH EMPHASIS ON CYTOMORPHOLOGY OF RARE METASTATIC MALIGNANCIES TO SEROUS CAVITY

Context: Serous effusion cytology is an important investigation for diagnosis of neoplastic and non-neoplastic diseases. Malignant cells in serous uid cytology indicates advanced stage. To evaluate the utility of serous ui Aims: d cytology in differential diagnosis of malignant and nonmalignant serous effusions and to emphasize the cytomorphology of rare metastatic malignancies. The importance of cell block with immunocytochemistry for diagnostically challenging cases was also highlighted. T Settings and Design: his was a one year retrospective study in which cases were classied into malignant and non-malignant. Immunohistochemistry was performed on cell blocks of difcult to diagnose cases. Methods and Material: Total 356 serous uids (pleural, peritoneal and pericardial uids) were centrifuged, cytocentrifuged and stained with Papanicolaou and Giemsa. Clinical history, radiological ndings and other relevant parameters were noted. 184 cases were of pleural Results: uid, 168 of peritoneal uid and four were of pericardial uid. Lung malignancies and ovarian malignancies were the most common primary sites in pleural and peritoneal uids respectively. Out of 40 positive for malignancy cases, 22 were rst conrmed on cytology. Clinical diagnosis of Boerhaave's syndrome was conrmed on cytology. Rare presentations of metastasis of squamous cell carcinoma, pleomorphic lobular carcinoma and clear cell type renal cell carcinoma were diagnosed on cytology. Rare m Conclusions: etastatic malignancies to serous cavity pose diagnostic challenges on cytology. Both, cytopathologists and clinicians should be aware of these rare malignancies. A vigilant cytopathologist can identify malignant cells based on cytomorphological features and give accurate diagnosis with the help of ancillary tests and lead clinicians for further work up, evaluation and treatment of the patients

Abstract P2-21-07: Exploring spatial correlations in Breast invasive Lobular Carcinoma subtypes using a novel CAF multiplex immunofluorescence panel

Abstract Background: Recent advances in immunotherapy led to development of new technologies to identify topographical distributions and correlations in the tumor microenvironment, enabling a better understanding of the tumor immune landscape. Based on the 2019 WHO classification Invasive lobular carcinoma (ILC) has various histological presentations. The pleomorphic variant has been reported to be biologically different to the classical counterpart. Cancer associated fibroblasts (CAFs) secrete cytokines and growth factors aiding in tumor growth. CAFs have been shown to express alpha-smooth muscle actin (α-SMA), Thy1, fibroblast activation protein (FAP), S-100. IHC based studies have shown differences in CAFs subpopulation between ILC and IDC. Here, we explored different CAFs subpopulations between Pleomorphic and Classical ILC using multiplex immunofluorescence (mIF). Study design: Multiplex immunofluorescence (mIF) was performed on formalin-fixed paraffin-embedded (FFPE) tissue sections [(n=6, classic ILC; n=6 pleomorphic ILC)] stained with Opal 7-color Kit using an automated system. Sections were stained consecutively with Pancytokeratin, CD45, A-SMA, FAP, S100, Thy-1. Slides were scanned using the Vectra 3.0 spectral imaging system (PerkinElmer). Five tumor ROIs were examined with Phenochart (Akoya/PerkinElmer) viewer and subsequent images were analyzed to explore spatial distances of CK+ cells to the CAFs. Data was generated using InForm and Phenoptr softwares (Akoya Labs) as a median value. Statistical analysis data correlation was performed using SPSS version 24.0 (IBM Corp) Results: Twelve invasive lobular carcinomas cases were evaluated. All cases with classical features were nuclear grade 2 and all pleomorphic cases (n=6) were nuclear grade 3. Six were Luminal B, five were Luminal A and one case was triple negative invasive lobular carcinoma. We studied nineteen different phenotypes of CAFs in the tumor, stroma, and overall tissue compartments. We found statistically significant differences (p-value&amp;lt; 0.05) between the distances of CAFs from the tumor cells in classic and pleomorphic ILC in three phenotypes. The A-SMA+, A-SMA+/S100+ phenotypes were closer to the tumor cells in classic subtype and the S100 only phenotype was closer to the tumor cells in pleomorphic carcinomas. In addition, there were two other phenotypes namely A-SMA+/Thy-1+(closer to tumor cells in classic ILC) and FAP+/S-100+ (closer to tumor cells in pleomorphic ILC), which showed a trend of significance (Table 1) Discussion: TME studies in invasive breast lobular carcinoma have been primarily based on chromogenic IHC. Multiplex immunofluorescence quantifies cell phenotype’s densities and positions in different tissue compartments (tumor vs stroma vs total tissue). Knowing the proximity of an individual TME cells to the tumor cells, aids in pinpointing possible therapeutic targets. Fibroblast dysregulation in cancers, enhances their pro-tumorigenic and anti-tumorigenic potential. Due to their heterogeneity, they can express a wide array of markers. Identifying the full possibility of CAF subsets is one of the keys to discovering actionable targets. Our results showed Alpha- SMA positive, Alpha-SMA/S-100 positive, Alpha SMA/Thy-1 positive CAFs in closer proximity to the classic ILC tumor cells as compared to pleomorphic ILC. Additionally, S-100 positive and FAP/S-100 positive CAFs showed a closer proximity to tumor cells in the pleomorphic subtype. Based on these results we hypothesize that pleomorphic ILCs are closely associated with pro-tumorigenic CAFs as compared to classic ILCs. Larger datasets are needed to confirm this. In conclusion we utilized an objective approach to quantify, phenotype and spatially correlate each cell in the tumor microenvironment. This has helped identifying CAFs subsets that differs in the spatial correlation to tumor cells in ILC subtypes, which can be potential actionable targets. Table 1 Phenotypes of Cancer associated fibroblasts and their statistical correlation between classic vs pleomorphic invasive Lobular carcinomas. Citation Format: Harsh Batra, Renganayaki K. Pandurengan, Heladio P. Ibarguen, Salome A McAllen, Qingqing Ding, Aysegul Sahin, Ignacio Wistuba, Edwin Roger Parra, Maria Gabriela Raso. Exploring spatial correlations in Breast invasive Lobular Carcinoma subtypes using a novel CAF multiplex immunofluorescence panel [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-21-07.

Abstract P6-04-16: ART: Automated Region segmentation of Tumor on HER2-stained breast cancer tissue

Abstract Background Computational pathology-based methods, eg, Quantitative Continuous Scoring (QCS) [Gustavson, SABCS 2020], are built to provide objective and quantitative methods to assess HER2 expression in breast cancer (BC). For accurate HER2 quantification, it is important to exclude non-invasive epithelium from analysis since HER2 overexpression could be more frequent in ductal carcinoma in situ (DCIS) and pleomorphic lobular carcinoma in situ (PLCIS) than in invasive BC [Lari, J Cancer 2011]. Generally, computational pathology-based approaches require experts to delineate the invasive BC regions of interest for analysis and exclude all benign/non-invasive epithelium. Developing a tool that delineates the invasive BC regions automatically without human intervention to avoid subjectivity of manual annotation by pathologists is ideal. We developed a novel, deep-learning–based system, called DualScaleNet, to perform Automated Region segmentation of Tumor (ART) by automatically identifying the invasive BC regions and excluding benign/non-invasive epithelium on HER2-stained digitized images. Identification and diagnosis of these regions, especially the in situ tumors are a challenge as they can mimic benign and invasive lesions causing wrong HER2 evaluation. Additional stains (eg, p63 for myoepithelial cells or laminin for basement membrane) are often required for diagnosis [Pinder, Mod Pathol 2010] but were not available for this study. Methods DualScaleNet works simultaneously on HER2-stained immunohistochemistry (IHC) image patches at 2 different resolutions. The target branch uses a higher resolution RGB image (0.5 μm/pixel) to learn accurate local details; the context branch uses a lower resolution image (4.0 μm/pixel) to incorporate more context in visual learning. The algorithm generates 4 output image layers representing probabilities of 4 classes: invasive tumor, ductal/lobular carcinoma in situ, benign epithelium, and other tissue. The final segmentation result is generated by assigning each image pixel the class with the largest probability value. The algorithm was trained using ground truth (GT) annotations generated by 5 pathologists using 6157 square field of views (FOVs), 200-500 μm in size. These FOVs were collected from 850 whole slide images (WSI), spanning 9 commercial BC sample cohorts stained with different HER2 assays and scanned by several versions of the Aperio AT2 scanner. The samples included a mixture of biopsies and resections and covered different BC histologies and HER2 staining intensities. To evaluate the reproducibility of tumor area detection by human pathologists, an interpathologist comparison in detection of invasive tumor regions was performed using 225 FOVs annotated by multiple pathologists. Results Analysis generated an average Dice/F1 Score of 81.6% among different pathologists for invasive cancer. On the same sample set (independent of the ART training set), the invasive cancer detection by the ART algorithm was on par with human pathologists, achieving a similar average Dice/F1 score of 80.7%. Conclusions Novel deep learning-based ART algorithm provides accurate segmentation of invasive cancer on HER2-stained IHC images. The performance was verified against the GT annotations provided by multiple pathologists. Since the algorithm is trained using annotations from multiple pathologists, it is not possible to generate higher accuracy with computational pathology than is achievable between independent pathologists. Importantly, the same WSI read by the ART will consistently output the exact same tumor region identification result thus removing the inherent human subjectivity and variability, while improving the turnaround time for analysis. This development serves as the necessary foundation upon which a computational pathology-based diagnostic can be built. Citation Format: Ansh Kapil, Anatoliy Shumilov, Philipp Wortmann, Sihem Khelifa, Jessica Chan, Michel Vandenberghe, Craig Barker, Mark Gustavson, Danielle Carroll, Hadassah Sade, Günter Schmidt. ART: Automated Region segmentation of Tumor on HER2-stained breast cancer tissue [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-04-16.

Abstract P2-23-11: Quantitative gene expression by RT-PCR in histologic subtypes of invasive breast carcinoma: an update in nearly one million cases

Abstract Background: Invasive ductal carcinoma (IDC) accounts for ~80% of all invasive breast carcinomas (IBC) with several histologic subtypes comprising the remainder of cases. Some histologic subtypes of IDC (such as tubular carcinoma) have been associated with better prognosis, while other subtypes (such as metaplastic and micropapillary) have been associated with poorer prognosis. Prior studies have shown patients with early stage, hormone-receptor positive IBC that have low Recurrence Score® (RS), as measured by the 21-gene Oncotype DX® (ODX) assay, have little benefit from chemotherapy. Here, we report our experience with the histologic subtypes of IDC and associated patterns of observed gene expression using ODX. Methods: All US samples submitted for IBC ODX between 2005 to 2021 were reviewed. Ductal carcinoma NOS (DC), tubular carcinoma (TC), cribriform carcinoma (CC), mucinous carcinoma (MUC), lobular carcinoma classic, solid or alveolar type (ILC), pleomorphic lobular carcinoma (PL), medullary/medullary-like carcinoma (MED), metaplastic carcinoma (MET), micropapillary carcinoma (MP), papillary carcinoma (PC) and solid papillary carcinoma (SPC) were included. Quantitative expression of 16 cancer-related genes was measured on a scale from 2 to 15 (relative to reference genes) where 1 unit increment is associated with ~2-fold change in expression. RS was calculated as published. Descriptive statistics for the RS, individual genes (ER, PR, HER2), and gene groups [invasion gene group (IGG) and proliferation gene group (PGG)] were obtained. Results: A total of 957,624 samples were included in this analysis with 85.4% DC, 9.7% ILC, 2.8% MUC, 0.5% TC, 0.4% PL, 0.4% PC, 0.3% MP, 0.2% CC, 0.2% MED, 0.1% SPC, and 0.02% MET. For all types, a wide continuous range of RS was noted. MET had the highest median RS, followed in decreasing order by MED, PL, DC &amp; ILC, TC, MUC, MP, CC, SPC, and PC. ER and PR were highest among PC and SPC. ER and PR were lowest among MED and MET. HER2 was highest among PC and TC and lowest among MED and MET. IGG was highest in MET and lowest in SPC. PGG was lowest for TC and highest for MED and MET. ER+/PR-/HER2- phenotype occurred more often in MED and PL. ER-/PR+/HER2- phenotype rarely occurred, but was most frequent in MED and MET. ER+/PR+/HER2+ accounted for 0.4% of our total sample. Conclusions: Here, we demonstrate histologic subtypes of IDC have a wide continuous range of RS. ODX assay may be used to further stratify patients with IDC and its histologic subtypes; however, further studies are needed to better understand the predictive capability of ODX in the histologic subtypes. Table 1. Quantitative gene expression by RT-PCR in histologic subtypes of invasive breast carcinoma Table 2. Biomarker profile in histologic subtypes of invasive breast carcinoma Citation Format: Nhu Thuy Can, Cynthia A. Flannery, Jess Hoag, Alekhya Akkunuri, Helen Bailey, Frederick Baehner. Quantitative gene expression by RT-PCR in histologic subtypes of invasive breast carcinoma: an update in nearly one million cases [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P2-23-11.

Cytological characteristics of histological types of lung cancer by cytomorphometric and flow cytometric analyses using liquid-based cytology materials.

Distinguishing the histological types of lung cancer is essential for determining treatment strategies in clinical practice. In this study, cytomorphological characteristics and proliferative activities were compared among histological types of lung cancer by cytomorphometric and flow cytometric analyses using liquid-based cytology (LBC) samples. Scraped LBC samples from 73 surgically resected specimens were collected between August 2018 and November 2019. Papanicolaou-stained and paired Ki-67-stained slides were used for cytomorphometric analyses. Another sample for each case was analyzed using a flow cytometric system (LC-1000). The cell proliferation index (CPIx) was calculated to evaluate proliferative activity. In total, 73 cases, including cases of adenocarcinoma (n=53), squamous cell carcinoma (n=14), small cell carcinoma (n=1), large cell neuroendocrine carcinoma (NEC; n=3), and pleomorphic carcinoma (n=2) were evaluated. Small cell carcinoma and large cell NEC were categorized into a single group, NEC. The adenocarcinoma group tended to have a larger nuclear area and longer perimeter than other histological types. The NEC group had a considerably higher Ki-67 labeling index and significantly higher CPIx than other histological types (p=.030). A significant positive correlation was observed between the Ki-67 labeling index and CPIx for all cases (r=0.362, p=.002). The Ki-67 labeling index and flow cytometric analyses focus on proliferative activity for the distinction of histological types of lung cancer, thereby guiding clinical decision-making.