Image analysis of immunohistochemistry-based biomarkers in breast cancer

Breast cancer is the leading form of cancer in women in Germany with about 69.000 new cases anually and a lifetime risk of 12.9%. One in eight women will develop a malignant neoplasm of the breast. Early diagnosis measures include regular clinical examinations, mammography and biopsies of suspicious lesions. Definite diagnosis is based on histopathology. Pathologic work-up encompasses histomorphology on H&E stained slides and a set of four biomarkers that provide prognostic information about the expected course of disease and predictive information about the likeliness to benefit from different clinical treatments. In breast cancer, immunohistochemistry is currently the most common type of biomarker. Immunohistochemistry conventionally relies on manual histological interpretation, but automated techniques based on image analysis have become increasingly available. In the present study, n = 613 breast cancer core needle biopsies from a single pathological laboratory (Pathologie Nordhessen, Kassel, Germany) were re-analysed by whole slide scanning of the histological specimens and image analysis of the biomarkers estrogen receptor, progesterone receptor, Her2 receptor and Ki-67 by the software package QuantCenter (3D Histech). The results were compared to manual biomarker interpretation by board-certified pathologists. Digitisation of the histological slides by a state-of-the-art tile scanner (3D Histech Pannoramic P250 Flash II) required 82 seconds per slide on average (standard deviation: ± 38s) and seemed technically mature. Allocation and storage of the large files constitute major issues that require costumised solutions. Image analysis did not work with out-of-the-box settings but required optimisation on local cases. After training of the software, satisfying rates of concordance were achived for estrogen and progesterone receptors with Cohen's kappa coefficients of κ = 0.86 and κ = 1.0. In Ki-67, systematic differences between manual scoring and image analysis were noticed and the best concordance achieved was κ = 0.68. Her2 yielded a good concordance of κ = 0.74 in a training set of n = 19 representative cases but only a moderate concordance of κ = 0.55 in the complete cohort. Exploratory analysis of Her2 yielded additional information on the physical basis of manual Her2 scoring. The findings indicate that image analysis is a mature technique that can be used to supplement the analysis of biomarkers in breast cancer. Image analysis has potential to decrease interobserver variance and to allow more precise quantitation. Yet, current software approaches require specific optimisation on local cases. The achieved concordance results from the representativeness of these training cases, which raises the question of how to define such reference standards. A possible solution could be centrally defined testing materials, for example tissue cultures with fixed levels of biomarker expression, that could be used for standardised local optimisation.2022-11-2

Digital Whole Slide Image Analysis of Elevated Stromal Content and Extracellular Matrix Protein Expression Predicts Adverse Prognosis in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis and limited treatment options. This study evaluates the prognostic value of stromal markers in TNBC, focusing on the tumor–stroma ratio (TSR) and overall stroma ratio (OSR) in whole slide images (WSI), as well as the expression of type-I collagen, type-III collagen, and fibrillin-1 on tissue microarrays (TMAs), using both visual assessment and digital image analysis (DIA). A total of 101 female TNBC patients, primarily treated with surgery between 2005 and 2016, were included. We found that high visual OSR correlates with worse overall survival (OS), advanced pN categories, lower stromal tumor-infiltrating lymphocyte count (sTIL), lower mitotic index, and patient age (p 45%), type-III collagen (>30%), and fibrillin-1 (>20%) were linked to significantly worse OS (p = 0.004, p = 0.013, and p = 0.005, respectively) and progression-free survival (PFS) (p = 0.028, p = 0.025, and p = 0.002, respectively), validated at the mRNA level. Our results highlight the importance of stromal characteristics in promoting tumor progression and metastasis and that targeting extracellular matrix (ECM) components may offer novel therapeutic strategies. Furthermore, DIA can be more accurate and objective in evaluating TSR, OSR, and immunodetected stromal markers than traditional visual examination

Mapping the immune environment in clear cell renal carcinoma by single-cell genomics

Clear cell renal cell carcinoma (ccRCC) is one of the most immunologically distinct tumor types due to high response rate to immunotherapies, despite low tumor mutational burden. To characterize the tumor immune microenvironment of ccRCC, we applied single-cell-RNA sequencing (SCRS) along with T-cell-receptor (TCR) sequencing to map the transcriptomic heterogeneity of 25,688 individual CD4

Enhanced ZnR/GPR39 activity in breast cancer, an alternative trigger of signaling leading to cell growth

Acquired resistance to the estrogen receptor (ER) antagonist tamoxifen, is a major obstacle in treatment of breast cancer. Changes in Zn2+ accumulation and distribution are associated with tamoxifen-resistance and breast cancer progression. The Zn2+-sensing G-protein coupled receptor, ZnR/GPR39, triggers signaling leading to cell growth, but a role for this receptor in breast cancer in unknown. Using fluorescence imaging, we found Zn2+-dependent Ca2+ release, mediated by ZnR/GPR39 activity, in TAMR tamoxifen-resistant cells derived from MCF-7 cells, but not in ER-expressing MCF-7 or T47D cells. Furthermore, ZnR/GPR39 signaling was monitored in ER negative BT20, MDA-MB-453 and JIMT-1 cells. Expression of ZnR/GPR39 was increased in grade 3 human breast cancer biopsies compared to grade 2. Consistently, analysis of two breast cancer patient cohorts, GDS4057 and TCGA, indicated that in ER-negative tumors higher ZnR/GPR39 mRNA levels are associated with more aggressive tumors. Activation of ZnR/GPR39 in TAMR cells triggered MAPK, mTOR and PI3K signaling. Importantly, enhanced cell growth and invasiveness was observed in the ER negative breast cancer cells, TAMR, MDA-MB-453 and BT20 cells but not in the ER expressing MCF-7 cells. Thus, we suggest ZnR/GPR39 as a potential therapeutic target for combination treatment in breast cancer, particularly relevant in ER negative tumors

Mucin MUC13 and YAP1 correlate with poor survival in colorectal cancer

Background: Metastatic disease contributes to over 90% of cancer-associated deaths. Colorectal cancer (CRC), the second lethal malignancy, has the greatest incidence and mortality rates in the Southern United States. Over 40-50% of CRC patients acquire metastasis at some point throughout their disease\u27s progression. CRC survival rate drops from 90%-14% when the disease is confined within the colon and therefore “early diagnosis” becomes imperative to determine timely and quality treatments. We have identified that MUC13 protein translocate to nucleus along with transcription factor Yes-Associated Protein 1 (YAP1) during anchorage independent conditions (metastatic phenotype). YAP1 is known to be overexpressed in CRC which promotes proliferation and survival of CRC cells. This study will provide information regarding MUC13 and YAP1 correlation and their role in CRC patient outcomes. Methods: The comparative analysis of MUC13 and YAP1 expression in CRC samples (Tissue Microarrays (TMA) of CRC patients (39 cases and 95 cores)) with Pathology grade, TNM Classification, Clinical stage, and Survival information were investigated using Immunohistochemistry (IHC) staining, followed by digital scanning by 3D-Histech scanner, and analysis using QuantCenter image analysis software. Results: IHC analysis revealed increased MUC13 expression in colon adenocarcinoma and metastatic adenocarcinoma compared to normal colon tissues. MUC13 expression was observed in nucleus, cytoplasm and membrane associated with mostly with poorly differentiated adenocarcinomas, while YAP1 was localized in the nucleus. The correlation of MUC13/YAP1 expression with patient outcome is in progress. Conclusion: This study will potentially establish a correlation between MUC13 and YAP1 with CRC patient outcome

Visual Counting and Automated Image-analytic Assessment of Ki-67 and their Prognostic Value in Synovial Sarcoma

BACKGROUND: Ki-67 is a widely used proliferation marker reflecting prognosis in various tumors. However, visual assessment and scoring of Ki-67 suffers from marked inter-observer and intra-observer variability. We aimed to assess the concordance of manual counting and automated image-analytic scoring methods for Ki-67 in synovial sarcoma. PATIENTS AND METHODS: Tissue microarrays from 34 patients with synovial sarcoma were immunostained for Ki-67 and scored both visually and with 3DHistech QuantCenter. RESULTS: The automated assessment of Ki-67 expression was in good agreement with the visually counted Ki-67 (r Pearson =0.96, p<0.001). In a Cox regression model automated [hazard ratio (HR)=1.047, p=0.024], but not visual (HR=1.063, p=0.053) assessment method associated high Ki-67 scores with worse overall survival. CONCLUSION: The automated Ki-67 assessment method appears to be comparable to the visual method in synovial sarcoma and had a significant association to overall survival.publishedVersionPeer reviewe

Artificial Intelligence-based Digital Pathology Assessment of CD44s Expression in Breast Cancer: Association with Clinicopathological Features and Survival Outcomes

Breast cancer (BC) exhibits considerable molecular and clinical heterogeneity, complicating prognostic evaluation. The cluster of differentiation 44 standard (CD44s) isoform has been proposed as a prognostic marker in various cancers; however, its role in BC remains unclear. This study evaluated CD44s expression in BC tissues and its association with clinicopathological features and survival outcomes using an artificial intelligence (AI)-based digital pathology scoring method. A retrospective analysis of 98 BC tissue samples is conducted, with CD44s cell membrane protein expression assessed through both manual and AI based immunohistochemical (IHC) scoring. Statistical analyses included Pearson’s chi-square test, Kaplan-Meier (log-rank), and Cox regression. CD44s expression was observed in 65.31% of patients. No significant associations are found between CD44s expression and clinicopathological characteristics, including age, tumor size, lymph node metastasis, histological grade, lymphovascular invasion (LVI), or hormone receptor status (all p &gt; 0.05). Survival analysis reveals no significant association between CD44s expression and overall survival (OS, p = 0.1345) or progression-free survival (p = 0.0669). While CD44s expression is prevalent in BC samples, it is not an independent prognostic factor; LVI is the only significant predictor of OS (p = 0.036). Finally, the moderate agreement between AI and manual scoring (Cohen’s Kappa = 0.4337, p &lt; 0.0001) supports the potential of AI-assisted methods for biomarker quantification, warranting further validation in larger cohorts

Semi-automated analysis of HER2 immunohistochemistry in invasive breast carcinoma using whole slide images: utility for interpretation in clinical practice

Human epidermal growth factor receptor 2 (HER2) gene amplification and subsequent protein overexpression is a strong prognostic and predictive biomarker in invasive breast carcinoma (IBC). ASCO/CAP recommended tests for HER2 assessment include immunohistochemistry (IHC) and/or in situ hybridization (ISH). Accurate HER2 IHC scoring (0, 1+, 2+, 3+) is key for appropriate classification and treatment of IBC. HER2-targeted therapies, including anti-HER2 monoclonal antibodies and antibody drug conjugates (ADC), have revolutionized the treatment of HER2-positive IBC. Recently, ADC have also been approved for treatment of HER2-low (IHC 1+, IHC 2+/ISH-) advanced breast carcinoma, making a distinction between IHC 0 and 1+ crucial. In this focused study, 32 IBC with HER2 IHC scores from 0 to 3+ and HER2 FISH results formed a calibration dataset, and 77 IBC with HER2 IHC score 2+ and paired FISH results (27 amplified, 50 non-amplified) formed a validation dataset. H&amp;E and HER2 IHC whole slide images (WSI) were scanned. Regions of interest were manually annotated and IHC scores generated by the software QuantCenter (MembraneQuant application) by 3DHISTECH Ltd. (Budapest, Hungary) and compared to the microscopic IHC score. H-scores [(3×%IHC3+) +(2×%IHC2+) +(1×%IHC1+)] were calculated for semi-automated (MembraneQuant) analysis. Concordance between microscopic IHC scoring and 3DHISTECH MembraneQuant semi-automated scoring in the calibration dataset showed a Kappa value of 0.77 (standard error 0.09). Microscopic IHC and MembraneQuant image analysis for the detection of HER2 amplification yielded a sensitivity of 100% for both and a specificity of 56% and 61%, respectively. In the validation set of IHC 2+ cases, only 13 of 77 cases (17%) had discordant results between microscopic and MembraneQuant images, and various artifacts limiting the interpretation of HER2 IHC, including cytoplasmic/granular staining and crush artifact were noted. Semi-automated analysis using WSI and microscopic evaluation yielded similar HER2 IHC scores, demonstrating the potential utility of this tool for interpretation in clinical practice and subsequent accurate treatment. In this study, it was shown that semi-automatic HER2 IHC interpretation provides an objective approach to a test known to be quite subjective

Quantitative Analysis of Carbonic Anhydrase IX Uncovers Hypoxia-Related Functional Differences in Classical Hodgkin Lymphoma Subtypes

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