Novel prognostic and predictive biomarkers for treatment decisions in breast and ovarian cancer
Breast Despite favorable 5-year survival rates, approximately 20% of breast cancer and 30% of early-stage ovarian cancer patients develop recurrence within five years after initial diagnosis. Additionally, there is currently no effective way to distinguish patients with varying clinical outcomes or may benefit from adjuvant treatment after surgery.
We hypothesize that for most patients, the genetic makeup of the primary tumor can predict aggressive tumor features that determine whether relapse may occur. To test this hypothesis, we studied the genetic signatures of a large cohort of breast and ovarian tumors and identified several potential novel biomarkers that can predict aggressive tumor behavior.
Our specific objectives are:
- to determine whether altered protein levels of the candidate biomarkers are associated with ovarian and breast cancer-specific survival, and different ovarian cancer histotypes.
- to define the tumorigenic and therapeutic potential of candidate biomarkers using patient-derived cancer cells and mouse models.
Our result will allow future improvement of the molecular classification of ovarian tumors in different histotype. Importantly, our work will shed light on the role of the identified biomarkers in tumor behavior and may provide valuable information for treatment strategies and guide decision-making process for breast and ovarian cancer treatment.
We use several molecular biology technologies to study tumor biology, including SNP-array, gene expression microarrays, RNA-Seq, DNA-Seq, DNA methylation, FISH, immunohistochemistry, cell transfection, and qPCR. In addition to clinical breast and ovarian tumor samples, we also use tumor cell lines, primary cells and mouse xenografts as model systems
Current group members
Khalil Helou, Associate Professor (Team Leader)
Per Karlsson, Professor (Oncologist)
Aniko Kovacs, Associate Professor (Pathologist)
Anna Fäldt Beding, PhD Student
Ella Ittner, PhD Student
Hugo Swenson, PhD Student
Luaay Aziz, PhD Student
Lucas Werner, PhD student
Elisabeth Werner Rönnerman, MD, PhD Student (Pathologist)
- A 17-marker panel for global genomic instability in breast cancer.
Biermann J, Nemes S, Parris TZ, Engqvist H, Rönnerman EW, Kovács A, Karlsson P, Helou K. Genomics. 2019 Jun 28. pii: S0888-7543(19)30225-3. doi: 10.1016/j.ygeno.2019.06.029.
- Radiation-induced genomic instability in breast carcinomas of the Swedish haemangioma cohort.
Biermann J, Langen B, Nemes S, Holmberg E, Parris TZ, Werner Rönnerman E, Engqvist H, Kovács A, Helou K, Karlsson P. Genes Chromosomes Cancer. 2019 Apr 2. doi: 10.1002/gcc.22757. [Epub ahead of print].
- Clonal relatedness in tumour pairs of breast cancer patients.
Biermann J, Parris TZ, Nemes S, Danielsson A, Engqvist H, Werner Rönnerman E, Forssell-Aronsson E, Kovács A, Karlsson P, Helou K. Breast Cancer Res. 2018 Aug 9;20(1):96. doi: 10.1186/s13058-018-1022-y.
- A Novel 18-Marker Panel Predicting Clinical Outcome in Breast Cancer.
Biermann J, Nemes S, Parris TZ, Engqvist H, Rönnerman EW, Forssell-Aronsson E, Steineck G, Karlsson P, Helou K. Cancer Epidemiol Biomarkers Prev. 2017 Nov;26(11):1619-1628. doi: 10.1158/1055-9965.EPI-17-0606.
- Frequent MYC coamplification and DNA hypomethylation of multiple genes on 8q in 8p11-p12-amplified breast carcinomas.
Parris TZ., Kovacs A, Hajizadeh S, Nemes S, Semaan M, Levin M, Karlsson P, Helou K. Oncogenesis. 2014 Mar 24;3:e95. doi: 10.1038/oncsis.2014.8.
- Additive effect of the AZGP1, PIP, S100A8, and UBE2C molecular biomarkers improves outcome prediction in breast carcinoma.
Parris TZ, Kovács A, Aziz L, Hajizadeh S, Nemes S, Semaan M, Forssell-Aronsson E, Karlsson P, Helou K. Int J Cancer. 2014 Apr 1;134(7):1617-29. doi: 10.1002/ijc.28497.
- A diagnostic algorithm to identify paired tumors with clonal origin.
Nemes S, Danielsson A, Parris TZ, Miao Jonasson J, Bulow E, Karlsson P, Steineck G, Helou K. Genes, chromosomes & cancer 2013 ;52(11):1007-16.
- Elevated cyclin B2 expression in invasive breast carcinoma is associated with unfavorable clinical outcome.
Shubbar E, Kovacs A, Hajizadeh S, Parris TZ, Nemes S, Gunnarsdottir K, Einbeigi Z, Karlsson P, Helou K. BMC cancer 2013, 13:1.
- Segmented regression, a versatile tool to analyze mRNA levels in relation to DNA copy number aberrations.
Nemes S, Parris TZ, Danielsson A, Kannius-Janson M, Jonasson JM, Steineck G, Helou K. Genes, chromosomes & cancer 2012, 51(1):77-82.
- Clinical implications of gene dosage and gene expression patterns in diploid breast carcinoma.
Parris TZ, Danielsson A, Nemes S, Kovacs A, Delle U, Fallenius G, Mollerstrom E, Karlsson P, Helou K. Clin Cancer Res 2010, 16(15):3860-3874.
More group Khalil Helou publications on PubMed