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A review of prognostic and predictive biomarkers in breast cancer

• Review Article
• Published: 15 January 2022
• Volume 23 , pages 1–16, ( 2023 )

Cite this article

• Elaheh Tarighati 1 ,
• Hadi Keivan 2 &
• Hojjat Mahani   ORCID: orcid.org/0000-0003-2696-0758 3  

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Breast cancer (BC) is a common cancer all over the world that affects women. BC is one of the leading causes of cancer mortality in women, which today has decreased with the advancement of technology and new diagnostic and therapeutic methods. BCs are histologically divided into in situ and invasive carcinoma, and both of them can be divided into ductal and lobular. The main function after the diagnosis of invasive breast cancer is which patient should use chemotherapy, which patient should receive adjuvant therapy, and which should not. If the decision is for adjuvant therapy, the next challenge is to identify the most appropriate treatment or combination of treatments for a particular patient. Addressing the first challenge can be helped by prognostic biomarkers, while addressing the second challenge can be done by predictive biomarkers. Among the molecular markers related to BC, ER, PR, HER2, and the Mib1/Ki-67 proliferation index are the most significant ones and are tightly confirmed in the standard care of all primary, recurrent, and metastatic BC patients. CEA and CA-15–3 antigens are the most valuable markers of serum tumors in BC patients. Determining the series of these markers helps monitor response to the treatment and early detection of recurrence or metastasis. miRNAs have been demonstrated to be intricate in mammary gland growth, proliferation, and formation of BC known to be incriminated in BC biology. By combining established prognostic factors with valid prognostic/predicted biomarkers, we can start the journey to personalized treatment for every recently diagnosed BC patient.

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Prognostic and Predictive Factors in Breast Carcinoma

Biomarkers in Breast Carcinomas

Prognostic and Predictive Factors of Invasive Breast Cancer

Abbreviations.

Aromatase inhibitors

American society of clinical oncology

• Breast cancer

Cancer antigen

Cyclin-dependent kinase 4/6

Carcinoembryonic antigen

Circulating tumor cells

Circulating tumor DNA

Ductal carcinoma in situ

Disease-free survival

Estradiol 2

Epidermal growth factor receptor

European Group on Tumor Markers

Estrogen receptor

Mutational status of ER

Endocrine therapy

Human epidermal growth factor receptor

Immunohistochemistry

Infiltrating lobular carcinoma

In situ hybridization

Lobular carcinoma in situ

National Cancer Institute

Overall survival

Positron emission tomography/computed tomography

Protein interacting with never in mitosis A

Progesterone receptor

Selective ER down-regulator

Selective ER modulator

Triple-negative BC

Untranslated region

Variant allele frequency

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Tarighati, E., Keivan, H. & Mahani, H. A review of prognostic and predictive biomarkers in breast cancer. Clin Exp Med 23 , 1–16 (2023). https://doi.org/10.1007/s10238-021-00781-1

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Electronic Theses and Dissertations

Computer aided diagnosis system for breast cancer using deep learning..

Asma Baccouche , University of Louisville Follow

Date on Master's Thesis/Doctoral Dissertation

Document type.

Doctoral Dissertation

Degree Name

Computer Engineering and Computer Science

Degree Program

Computer Science and Engineering, PhD

Committee Chair

Elmaghraby, Adel

Committee Co-Chair (if applicable)

Garcia-Zapirain, Maria Begona

Committee Member

Sierra-Sosa, Daniel

Gentili, Monica

Park, Juw Won

Author's Keywords

Medical imaging; breast cancer; deep learning; CAD; artificial intelligence; computer vision

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous applications provided efficient solutions to assist radiologists and doctors for medical imaging analysis, which has remained the essence of the visual representation that is used to construct the final observation and diagnosis. Medical research in cancerology and oncology has been recently blended with the knowledge gained from computer engineering and data science experts. In this context, an automatic assistance or commonly known as Computer-aided Diagnosis (CAD) system has become a popular area of research and development in the last decades. As a result, the CAD systems have been developed using multidisciplinary knowledge and expertise and they have been used to analyze the patient information to assist clinicians and practitioners in their decision-making process. Treating and preventing cancer remains a crucial task that radiologists and oncologists face every day to detect and investigate abnormal tumors. Therefore, a CAD system could be developed to provide decision support for many applications in the cancer patient care processes, such as lesion detection, characterization, cancer staging, tumors assessment, recurrence, and prognosis prediction. Breast cancer has been considered one of the common types of cancers in females across the world. It was also considered the leading cause of mortality among women, and it has been increased drastically every year. Early detection and diagnosis of abnormalities in screened breasts has been acknowledged as the optimal solution to examine the risk of developing breast cancer and thus reduce the increasing mortality rate. Accordingly, this dissertation proposes a new state-of-the-art CAD system for breast cancer diagnosis that is based on deep learning technology and cutting-edge computer vision techniques. Mammography screening has been recognized as the most effective tool to early detect breast lesions for reducing the mortality rate. It helps reveal abnormalities in the breast such as Mass lesion, Architectural Distortion, Microcalcification. With the number of daily patients that were screened is continuously increasing, having a second reading tool or assistance system could leverage the process of breast cancer diagnosis. Mammograms could be obtained using different modalities such as X-ray scanner and Full-Field Digital mammography (FFDM) system. The quality of the mammograms, the characteristics of the breast (i.e., density, size) or/and the tumors (i.e., location, size, shape) could affect the final diagnosis. Therefore, radiologists could miss the lesions and consequently they could generate false detection and diagnosis. Therefore, this work was motivated to improve the reading of mammograms in order to increase the accuracy of the challenging tasks. The efforts presented in this work consists of new design and implementation of neural network models for a fully integrated CAD system dedicated to breast cancer diagnosis. The approach is designed to automatically detect and identify breast lesions from the entire mammograms at a first step using fusion models’ methodology. Then, the second step only focuses on the Mass lesions and thus the proposed system should segment the detected bounding boxes of the Mass lesions to mask their background. A new neural network architecture for mass segmentation was suggested that was integrated with a new data enhancement and augmentation technique. Finally, a third stage was conducted using a stacked ensemble of neural networks for classifying and diagnosing the pathology (i.e., malignant, or benign), the Breast Imaging Reporting and Data System (BI-RADS) assessment score (i.e., from 2 to 6), or/and the shape (i.e., round, oval, lobulated, irregular) of the segmented breast lesions. Another contribution was achieved by applying the first stage of the CAD system for a retrospective analysis and comparison of the model on Prior mammograms of a private dataset. The work was conducted by joining the learning of the detection and classification model with the image-to-image mapping between Prior and Current screening views. Each step presented in the CAD system was evaluated and tested on public and private datasets and consequently the results have been fairly compared with benchmark mammography datasets. The integrated framework for the CAD system was also tested for deployment and showcase. The performance of the CAD system for the detection and identification of breast masses reached an overall accuracy of 97%. The segmentation of breast masses was evaluated together with the previous stage and the approach achieved an overall performance of 92%. Finally, the classification and diagnosis step that defines the outcome of the CAD system reached an overall pathology classification accuracy of 96%, a BIRADS categorization accuracy of 93%, and a shape classification accuracy of 90%. Results given in this dissertation indicate that our suggested integrated framework might surpass the current deep learning approaches by using all the proposed automated steps. Limitations of the proposed work could occur on the long training time of the different methods which is due to the high computation of the developed neural networks that have a huge number of the trainable parameters. Future works can include new orientations of the methodologies by combining different mammography datasets and improving the long training of deep learning models. Moreover, motivations could upgrade the CAD system by using annotated datasets to integrate more breast cancer lesions such as Calcification and Architectural distortion. The proposed framework was first developed to help detect and identify suspicious breast lesions in X-ray mammograms. Next, the work focused only on Mass lesions and segment the detected ROIs to remove the tumor’s background and highlight the contours, the texture, and the shape of the lesions. Finally, the diagnostic decision was predicted to classify the pathology of the lesions and investigate other characteristics such as the tumors’ grading assessment and type of the shape. The dissertation presented a CAD system to assist doctors and experts to identify the risk of breast cancer presence. Overall, the proposed CAD method incorporates the advances of image processing, deep learning, and image-to-image translation for a biomedical application.

Recommended Citation

Baccouche, Asma, "Computer aided diagnosis system for breast cancer using deep learning." (2022). Electronic Theses and Dissertations. Paper 3931. https://doi.org/10.18297/etd/3931

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Theses/dissertations from 2023 2023.

Development of Combination Therapy Strategies to Treat Cancer Using Dihydroorotate Dehydrogenase Inhibitors , Nicholas Mullen

Overcoming Resistance Mechanisms to CDK4/6 Inhibitor Treatment Using CDK6-Selective PROTAC , Sarah Truong

Theses/Dissertations from 2022 2022

Omics Analysis in Cancer and Development , Emalie J. Clement

Investigating the Role of Splenic Macrophages in Pancreatic Cancer , Daisy V. Gonzalez

Polymeric Chloroquine in Metastatic Pancreatic Cancer Therapy , Rubayat Islam Khan

Evaluating Targets and Therapeutics for the Treatment of Pancreatic Cancer , Shelby M. Knoche

Characterization of 1,1-Diarylethylene FOXM1 Inhibitors Against High-Grade Serous Ovarian Carcinoma Cells , Cassie Liu

Novel Mechanisms of Protein Kinase C α Regulation and Function , Xinyue Li

SOX2 Dosage Governs Tumor Cell Identity and Proliferation , Ethan P. Metz

Post-Transcriptional Control of the Epithelial-to-Mesenchymal Transition (EMT) in Ras-Driven Colorectal Cancers , Chaitra Rao

Use of Machine Learning Algorithms and Highly Multiplexed Immunohistochemistry to Perform In-Depth Characterization of Primary Pancreatic Tumors and Metastatic Sites , Krysten Vance

Characterization of Metastatic Cutaneous Squamous Cell Carcinoma in the Immunosuppressed Patient , Megan E. Wackel

Visceral adipose tissue remodeling in pancreatic ductal adenocarcinoma cachexia: the role of activin A signaling , Pauline Xu

Phos-Tag-Based Screens Identify Novel Therapeutic Targets in Ovarian Cancer and Pancreatic Cancer , Renya Zeng

Theses/Dissertations from 2021 2021

Functional Characterization of Cancer-Associated DNA Polymerase ε Variants , Stephanie R. Barbari

Pancreatic Cancer: Novel Therapy, Research Tools, and Educational Outreach , Ayrianne J. Crawford

Apixaban to Prevent Thrombosis in Adult Patients Treated With Asparaginase , Krishna Gundabolu

Molecular Investigation into the Biologic and Prognostic Elements of Peripheral T-cell Lymphoma with Regulators of Tumor Microenvironment Signaling Explored in Model Systems , Tyler Herek

Utilizing Proteolysis-Targeting Chimeras to Target the Transcriptional Cyclin-Dependent Kinases 9 and 12 , Hannah King

Insights into Cutaneous Squamous Cell Carcinoma Pathogenesis and Metastasis Using a Bedside-to-Bench Approach , Marissa Lobl

Development of a MUC16-Targeted Near-Infrared Antibody Probe for Fluorescence-Guided Surgery of Pancreatic Cancer , Madeline T. Olson

FGFR4 glycosylation and processing in cholangiocarcinoma promote cancer signaling , Andrew J. Phillips

Theses/Dissertations from 2020 2020

Cooperativity of CCNE1 and FOXM1 in High-Grade Serous Ovarian Cancer , Lucy Elge

Characterizing the critical role of metabolic and redox homeostasis in colorectal cancer , Danielle Frodyma

Genomic and Transcriptomic Alterations in Metabolic Regulators and Implications for Anti-tumoral Immune Response , Ryan J. King

Dimers of Isatin Derived Spirocyclic NF-κB Inhibitor Exhibit Potent Anticancer Activity by Inducing UPR Mediated Apoptosis , Smit Kour

From Development to Therapy: A Panoramic Approach to Further Our Understanding of Cancer , Brittany Poelaert

The Cellular Origin and Molecular Drivers of Claudin-Low Mammary Cancer , Patrick D. Raedler

Mitochondrial Metabolism as a Therapeutic Target for Pancreatic Cancer , Simon Shin

Development of Fluorescent Hyaluronic Acid Nanoparticles for Intraoperative Tumor Detection , Nicholas E. Wojtynek

Theses/Dissertations from 2019 2019

The role of E3 ubiquitin ligase FBXO9 in normal and malignant hematopoiesis , R. Willow Hynes-Smith

BRCA1 & CTDP1 BRCT Domainomics in the DNA Damage Response , Kimiko L. Krieger

Targeted Inhibition of Histone Deacetyltransferases for Pancreatic Cancer Therapy , Richard Laschanzky

Human Leukocyte Antigen (HLA) Class I Molecule Components and Amyloid Precursor-Like Protein 2 (APLP2): Roles in Pancreatic Cancer Cell Migration , Bailee Sliker

Theses/Dissertations from 2018 2018

FOXM1 Expression and Contribution to Genomic Instability and Chemoresistance in High-Grade Serous Ovarian Cancer , Carter J. Barger

Overcoming TCF4-Driven BCR Signaling in Diffuse Large B-Cell Lymphoma , Keenan Hartert

Functional Role of Protein Kinase C Alpha in Endometrial Carcinogenesis , Alice Hsu

Functional Signature Ontology-Based Identification and Validation of Novel Therapeutic Targets and Natural Products for the Treatment of Cancer , Beth Neilsen

Elucidating the Roles of Lunatic Fringe in Pancreatic Ductal Adenocarcinoma , Prathamesh Patil

Theses/Dissertations from 2017 2017

Metabolic Reprogramming of Pancreatic Ductal Adenocarcinoma Cells in Response to Chronic Low pH Stress , Jaime Abrego

Understanding the Relationship between TGF-Beta and IGF-1R Signaling in Colorectal Cancer , Katie L. Bailey

The Role of EHD2 in Triple-Negative Breast Cancer Tumorigenesis and Progression , Timothy A. Bielecki

Perturbing anti-apoptotic proteins to develop novel cancer therapies , Jacob Contreras

Role of Ezrin in Colorectal Cancer Cell Survival Regulation , Premila Leiphrakpam

Evaluation of Aminopyrazole Analogs as Cyclin-Dependent Kinase Inhibitors for Colorectal Cancer Therapy , Caroline Robb

Identifying the Role of Janus Kinase 1 in Mammary Gland Development and Breast Cancer , Barbara Swenson

DNMT3A Haploinsufficiency Provokes Hematologic Malignancy of B-Lymphoid, T-Lymphoid, and Myeloid Lineage in Mice , Garland Michael Upchurch

Theses/Dissertations from 2016 2016

EHD1 As a Positive Regulator of Macrophage Colony-Stimulating Factor-1 Receptor , Luke R. Cypher

Inflammation- and Cancer-Associated Neurolymphatic Remodeling and Cachexia in Pancreatic Ductal Adenocarcinoma , Darci M. Fink

Role of CBL-family Ubiquitin Ligases as Critical Negative Regulators of T Cell Activation and Functions , Benjamin Goetz

Exploration into the Functional Impact of MUC1 on the Formation and Regulation of Transcriptional Complexes Containing AP-1 and p53 , Ryan L. Hanson

DNA Polymerase Zeta-Dependent Mutagenesis: Molecular Specificity, Extent of Error-Prone Synthesis, and the Role of dNTP Pools , Olga V. Kochenova

Defining the Role of Phosphorylation and Dephosphorylation in the Regulation of Gap Junction Proteins , Hanjun Li

Molecular Mechanisms Regulating MYC and PGC1β Expression in Colon Cancer , Jamie L. McCall

Pancreatic Cancer Invasion of the Lymphatic Vasculature and Contributions of the Tumor Microenvironment: Roles for E-selectin and CXCR4 , Maria M. Steele

Altered Levels of SOX2, and Its Associated Protein Musashi2, Disrupt Critical Cell Functions in Cancer and Embryonic Stem Cells , Erin L. Wuebben

Theses/Dissertations from 2015 2015

Characterization and target identification of non-toxic IKKβ inhibitors for anticancer therapy , Elizabeth Blowers

Effectors of Ras and KSR1 dependent colon tumorigenesis , Binita Das

Characterization of cancer-associated DNA polymerase delta variants , Tony M. Mertz

A Role for EHD Family Endocytic Regulators in Endothelial Biology , Alexandra E. J. Moffitt

Biochemical pathways regulating mammary epithelial cell homeostasis and differentiation , Chandrani Mukhopadhyay

EPACs: epigenetic regulators that affect cell survival in cancer. , Catherine Murari

Role of the C-terminus of the Catalytic Subunit of Translesion Synthesis Polymerase ζ (Zeta) in UV-induced Mutagensis , Hollie M. Siebler

LGR5 Activates TGFbeta Signaling and Suppresses Metastasis in Colon Cancer , Xiaolin Zhou

LGR5 Activates TGFβ Signaling and Suppresses Metastasis in Colon Cancer , Xiaolin Zhou

Theses/Dissertations from 2014 2014

Genetic dissection of the role of CBL-family ubiquitin ligases and their associated adapters in epidermal growth factor receptor endocytosis , Gulzar Ahmad

Strategies for the identification of chemical probes to study signaling pathways , Jamie Leigh Arnst

Defining the mechanism of signaling through the C-terminus of MUC1 , Roger B. Brown

Targeting telomerase in human pancreatic cancer cells , Katrina Burchett

The identification of KSR1-like molecules in ras-addicted colorectal cancer cells , Drew Gehring

Mechanisms of regulation of AID APOBEC deaminases activity and protection of the genome from promiscuous deamination , Artem Georgievich Lada

Characterization of the DNA-biding properties of human telomeric proteins , Amanda Lakamp-Hawley

Studies on MUC1, p120-catenin, Kaiso: coordinate role of mucins, cell adhesion molecules and cell cycle players in pancreatic cancer , Xiang Liu

Epac interaction with the TGFbeta PKA pathway to regulate cell survival in colon cancer , Meghan Lynn Mendick

Theses/Dissertations from 2013 2013

Deconvolution of the phosphorylation patterns of replication protein A by the DNA damage response to breaks , Kerry D. Brader

Modeling malignant breast cancer occurrence and survival in black and white women , Michael Gleason

The role of dna methyltransferases in myc-induced lymphomagenesis , Ryan A. Hlady

Design and development of inhibitors of CBL (TKB)-protein interactions , Eric A. Kumar

Pancreatic cancer-associated miRNAs : expression, regulation and function , Ashley M. Mohr

Mechanistic studies of mitochondrial outer membrane permeabilization (MOMP) , Xiaming Pang

Novel roles for JAK2/STAT5 signaling in mammary gland development, cancer, and immune dysregulation , Jeffrey Wayne Schmidt

Optimization of therapeutics against lethal pancreatic cancer , Joshua J. Souchek

Theses/Dissertations from 2012 2012

Immune-based novel diagnostic mechanisms for pancreatic cancer , Michael J. Baine

Sox2 associated proteins are essential for cell fate , Jesse Lee Cox

KSR2 regulates cellular proliferation, transformation, and metabolism , Mario R. Fernandez

Discovery of a novel signaling cross-talk between TPX2 and the aurora kinases during mitosis , Jyoti Iyer

Regulation of metabolism by KSR proteins , Paula Jean Klutho

The role of ERK 1/2 signaling in the dna damage-induced G2 , Ryan Kolb

Regulation of the Bcl-2 family network during apoptosis induced by different stimuli , Hernando Lopez

Studies on the role of cullin3 in mitosis , Saili Moghe

Characteristics of amyloid precursor-like protein 2 (APLP2) in pancreatic cancer and Ewing's sarcoma , Haley Louise Capek Peters

Structural and biophysical analysis of a human inosine triphosphate pyrophosphatase polymorphism , Peter David Simone

Functions and regulation of Ron receptor tyrosine kinase in human pancreatic cancer and its therapeutic applications , Yi Zou

Theses/Dissertations from 2011 2011

Coordinate detection of new targets and small molecules for cancer therapy , Kurt Fisher

The role of c-Myc in pancreatic cancer initiation and progression , Wan-Chi Lin

The role of inosine triphosphate pyrophosphatase (ITPA) in maintanence [sic] of genomic stability in human cells , Miriam-Rose Menezes

Molecular insights into major histocompatibility complex class I folding and assembly , Laura Christina Simone

The role of bcl-2 in colon cancer metastatic progression , Wang Wang

A rational peptidomimetic approach towards generation of high affinity BRCT (BRCA1) inhibitors , Ziyan Yuan

D-type cyclins and breast cancer , Quian Zhang

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