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Raj-Kumar PK, Lin X, Liu T, Sturtz LA, Gritsenko MA, Petyuk VA, Sagendorf TJ, Deyarmin B, Liu J, Praveen-Kumar A, Wang G, McDermott JE, Shukla AK, Moore RJ, Monroe ME, Webb-Robertson BJM, Hooke JA, Fantacone-Campbell L, Mostoller B, Kvecher L, Kane J, Melley J, Somiari S, Soon-Shiong P, Smith RD, Mural RJ, Rodland KD, Shriver CD, Kovatich AJ, Hu H. Proteogenomic characterization of difficult-to-treat breast cancer with tumor cells enriched through laser microdissection. Breast Cancer Res 2024; 26:76. [PMID: 38745208 PMCID: PMC11094977 DOI: 10.1186/s13058-024-01835-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 05/05/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. METHODS We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. RESULTS We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations in TP53, PLXNB3, Zinc finger genes, and fewer mutations in SDC2, CDH1, PIK3CA, SVIL, and PTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA-protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, including KIAA1522, DCK, FOXO3, MYO9B, ARID1A, EPRS, ZC3HAV1, and RBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. CONCLUSIONS This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.
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Affiliation(s)
- Praveen-Kumar Raj-Kumar
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Xiaoying Lin
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Tao Liu
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Lori A Sturtz
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | | | | | | | - Brenda Deyarmin
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | - Jianfang Liu
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | | | - Guisong Wang
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | | | - Anil K Shukla
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Ronald J Moore
- Pacific Northwest National Laboratory, Richland, WA, USA
| | | | | | - Jeffrey A Hooke
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Leigh Fantacone-Campbell
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Brad Mostoller
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | - Leonid Kvecher
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Jennifer Kane
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | - Jennifer Melley
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | - Stella Somiari
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | | | | | - Richard J Mural
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA
| | | | - Craig D Shriver
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
- Department of Surgery, Walter Reed National Military Medical Center, Bethesda, MD, USA.
| | - Albert J Kovatich
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Hai Hu
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, PA, USA.
- Murtha Cancer Center Research Program, Department of Surgery, Uniformed Services University of the Health Sciences, Bethesda, MD, USA.
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Oblak T, Škerl P, Narang BJ, Blagus R, Krajc M, Novaković S, Žgajnar J. Breast cancer risk prediction using Tyrer-Cuzick algorithm with an 18-SNPs polygenic risk score in a European population with below-average breast cancer incidence. Breast 2023; 72:103590. [PMID: 37857130 PMCID: PMC10587756 DOI: 10.1016/j.breast.2023.103590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 09/27/2023] [Accepted: 10/09/2023] [Indexed: 10/21/2023] Open
Abstract
GOALS To determine whether an 18 single nucleotide polymorphisms (SNPs) polygenic risk score (PRS18) improves breast cancer (BC) risk prediction for women at above-average risk of BC, aged 40-49, in a Central European population with BC incidence below EU average. METHODS 502 women aged 40-49 years at the time of BC diagnosis completed a questionnaire on BC risk factors (as per Tyrer-Cuzick algorithm) with data known at age 40 and before BC diagnosis. Blood samples were collected for DNA isolation. 250 DNA samples from healthy women aged 50 served as a control cohort. 18 BC-associated SNPs were genotyped in both groups and PRS18 was calculated. The predictive power of PRS18 to detect BC was evaluated using a ROC curve. 10-year BC risk was calculated using the Tyrer-Cuzick algorithm adapted to the Slovenian incidence rate (S-IBIS): first based on questionnaire-based risk factors and, second, including PRS18. RESULTS The AUC for PRS18 was 0.613 (95 % CI 0.570-0.657). 83.3 % of women were classified at above-average risk for BC with S-IBIS without PRS18 and 80.7 % when PRS18 was included. CONCLUSION BC risk prediction models and SNPs panels should not be automatically used in clinical practice in different populations without prior population-based validation. In our population the addition of an 18SNPs PRS to questionnaire-based risk factors in the Tyrer-Cuzick algorithm in general did not improve BC risk stratification, however, some improvements were observed at higher BC risk scores and could be valuable in distinguishing women at intermediate and high risk of BC.
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Affiliation(s)
- Tjaša Oblak
- Department of Surgical Oncology, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia; Medical Faculty, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia.
| | - Petra Škerl
- Department of Molecular Diagnostics, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
| | - Benjamin J Narang
- Institute for Biostatistics and Medical Informatics, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia; Department of Automatics, Jožef Stefan Institute, Biocybernetics and Robotics, Jamova cesta 39, Ljubljana, Slovenia; Faculty of Sport, University of Ljubljana, Gortanova 22, Ljubljana, Slovenia.
| | - Rok Blagus
- Institute for Biostatistics and Medical Informatics, University of Ljubljana, Vrazov trg 2, 1000, Ljubljana, Slovenia; Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, 6000, Koper, Slovenia.
| | - Mateja Krajc
- Cancer Genetics Clinic, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
| | - Srdjan Novaković
- Department of Molecular Diagnostics, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
| | - Janez Žgajnar
- Department of Surgical Oncology, Institute of Oncology Ljubljana, Zaloška cesta 2, 1000, Ljubljana, Slovenia.
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Ugalde‐Morales E, Grassmann F, Humphreys K, Li J, Eriksson M, Tobin NP, Borg Å, Vallon‐Christersson J, Hall P, Czene K. Association between breast cancer risk and disease aggressiveness: Characterizing underlying gene expression patterns. Int J Cancer 2020; 148:884-894. [PMID: 32856720 PMCID: PMC7818270 DOI: 10.1002/ijc.33270] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Revised: 08/12/2020] [Accepted: 08/13/2020] [Indexed: 12/12/2022]
Abstract
The association between breast cancer risk defined by the Tyrer-Cuzick score (TC) and disease prognosis is not well established. Here, we investigated the relationship between 5-year TC and disease aggressiveness and then characterized underlying molecular processes. In a case-only study (n = 2474), we studied the association of TC with molecular subtypes and tumor characteristics. In a subset of patients (n = 672), we correlated gene expression to TC and computed a low-risk TC gene expression (TC-Gx) profile, that is, a profile expected to be negatively associated with risk, which we used to test for association with disease aggressiveness. We performed enrichment analysis to pinpoint molecular processes likely to be altered in low-risk tumors. A higher TC was found to be inversely associated with more aggressive surrogate molecular subtypes and tumor characteristics (P < .05) including Ki-67 proliferation status (P < 5 × 10-07 ). Our low-risk TC-Gx, based on the weighted sum of 37 expression values of genes strongly correlated with TC, was associated with basal-like (P < 5 × 10-13 ), HER2-enriched subtype (P < 5 × 10-07 ) and worse 10-year breast cancer-specific survival (log-rank P < 5 × 10-04 ). Associations between low-risk TC-Gx and more aggressive molecular subtypes were replicated in an independent cohort from The Cancer Genome Atlas database (n = 975). Gene expression that correlated with low TC was enriched in proliferation and oncogenic signaling pathways (FDR < 0.05). Moreover, higher proliferation was a key factor explaining the association with worse survival. Women who developed breast cancer despite having a low risk were diagnosed with more aggressive tumors and had a worse prognosis, most likely driven by increased proliferation. Our findings imply the need to establish risk factors associated with more aggressive breast cancer subtypes.
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Affiliation(s)
- Emilio Ugalde‐Morales
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Felix Grassmann
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Institute of Medical SciencesUniversity of AberdeenAberdeenUK
| | - Keith Humphreys
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Swedish eScience Research Centre (SeRC)Karolinska InstitutetStockholmSweden
| | - Jingmei Li
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of Human GeneticsGenome Institute of SingaporeSingaporeSingapore
- Department of Surgery, Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
| | - Mikael Eriksson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Nicholas P. Tobin
- Department of Oncology‐PathologyKarolinska InstitutetStockholmSweden
| | - Åke Borg
- Department of Clinical Sciences, Division of Oncology and PathologyLund UniversityLundSweden
- Department of OncologyLund University Cancer CenterLundSweden
- CREATE Health Strategic Centre for Translational Cancer ResearchLund UniversityLundSweden
- Department of Clinical Sciences, SCIBLU GenomicsLund UniversityLundSweden
| | - Johan Vallon‐Christersson
- Department of Clinical Sciences, Division of Oncology and PathologyLund UniversityLundSweden
- Department of OncologyLund University Cancer CenterLundSweden
- CREATE Health Strategic Centre for Translational Cancer ResearchLund UniversityLundSweden
| | - Per Hall
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of OncologySödersjukhusetStockholmSweden
| | - Kamila Czene
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
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