Johan Hartman's Group
Precision pathology and tumor heterogeneity
Breast cancer remains to be the most common malignancy for women in Sweden. Great improvements in screening and adjuvant therapy have led to a current 5-year survival rate of 90%. The individual treatment strategy is based on routine biomarkers on immunohistochemical level; estrogen receptor (ER), progesterone receptor (PR), Her2 and Ki67. ER expression confers strong indications for response to endocrine therapy, whereas patients with Her2-overexpressing tumors can be effectively treated with anti-Her2 therapy. However, such management of breast cancer patients is insufficient to distinguish resistant tumors. We use a variety of methods to identify patterns of drug resistance. Our projects are all of translational character and goes from in vitro experimental models to studies on patient material ex vivo. We are also very interested in the role of tumor-metastatic heterogeneity in relation to drug response.
Group members
Johan Hartman, Professor, Group leader
Emelie Karlsson, Research Coordinator
Stephanie Robertson, MD, PhD, postdoc
Caroline Rönnlund, MD, PhD student
Caroline Schagerholm, MD, PhD student
Qiao Yang, PhD student
Sanna Steen, MD, PhD student
Balazs Acs, MD, PhD, Postdoc
Xinsong Chen, Postdoc
Elin Hardell, MD, PhD, Postdoc
Ceren Boyaci, MD, Affiliated
Wenwen Sun, Affiliated
Helena Olofsson, Affiliated
Selected publications
Transcriptional intra-tumour heterogeneity predicted by deep learning in routine breast histopathology slides provides independent prognostic information.
Wang Y, Ali MA, Vallon-Christersson J, Humphreys K, Hartman J, Rantalainen M
Eur J Cancer 2023 Jun;191():112953
Predicting Molecular Phenotypes from Histopathology Images: A Transcriptome-Wide Expression-Morphology Analysis in Breast Cancer.
Wang Y, Kartasalo K, Weitz P, Ács B, Valkonen M, Larsson C, Ruusuvuori P, Hartman J, Rantalainen M
Cancer Res 2021 Oct;81(19):5115-5126
Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction.
Chen X, Sifakis EG, Robertson S, Neo SY, Jun SH, Tong L, Hui Min AT, Lövrot J, Hellgren R, Margolin S, Bergh J, Foukakis T, Lagergren J, Lundqvist A, Ma R, Hartman J
Proc Natl Acad Sci U S A 2023 Jan;120(1):e2209856120
Improved breast cancer histological grading using deep learning.
Wang Y, Acs B, Robertson S, Liu B, Solorzano L, Wählby C, Hartman J, Rantalainen M
Ann Oncol 2022 Jan;33(1):89-98
CD73 immune checkpoint defines regulatory NK cells within the tumor microenvironment.
Neo SY, Yang Y, Record J, Ma R, Chen X, Chen Z, Tobin NP, Blake E, Seitz C, Thomas R, Wagner AK, Andersson J, de Boniface J, Bergh J, Murray S, Alici E, Childs R, Johansson M, Westerberg LS, Haglund F, Hartman J, Lundqvist A
J Clin Invest 2020 Mar;130(3):1185-1198
Variability in Breast Cancer Biomarker Assessment and the Effect on Oncological Treatment Decisions: A Nationwide 5-Year Population-Based Study.
Acs B, Fredriksson I, Rönnlund C, Hagerling C, Ehinger A, Kovács A, Røge R, Bergh J, Hartman J
Cancers (Basel) 2021 Mar;13(5):
Predicting molecular phenotypes from histopathology images: a transcriptome-wide expression-morphology analysis in breast cancer.
Wang Y, Kartasalo K, Weitz P, Acs B, Valkonen M, Larsson C, Ruusuvuori P, Hartman J, Rantalainen M
Cancer Res 2021 Aug;():
CD73 immune checkpoint defines regulatory NK cells within the tumor microenvironment.
Neo SY, Yang Y, Record J, Ma R, Chen X, Chen Z, Tobin NP, Blake E, Seitz C, Thomas R, Wagner AK, Andersson J, de Boniface J, Bergh J, Murray S, Alici E, Childs R, Johansson M, Westerberg LS, Haglund F, Hartman J, Lundqvist A
J Clin Invest 2020 03;130(3):1185-1198
Evolutionary history of metastatic breast cancer reveals minimal seeding from axillary lymph nodes.
Ullah I, Karthik GM, Alkodsi A, Kjällquist U, Stålhammar G, Lövrot J, et al
J. Clin. Invest. 2018 Apr;128(4):1355-1370
Estrogen Receptor β as a Therapeutic Target in Breast Cancer Stem Cells.
Ma R, Karthik GM, Lövrot J, Haglund F, Rosin G, Katchy A, et al
J. Natl. Cancer Inst. 2017 03;109(3):1-14
Sequencing-based breast cancer diagnostics as an alternative to routine biomarkers.
Rantalainen M, Klevebring D, Lindberg J, Ivansson E, Rosin G, Kis L, et al
Sci Rep 2016 11;6():38037
Digital image analysis outperforms manual biomarker assessment in breast cancer.
Stålhammar G, Fuentes Martinez N, Lippert M, Tobin NP, Mølholm I, Kis L, et al
Mod. Pathol. 2016 Apr;29(4):318-29
mTOR inhibitors counteract tamoxifen-induced activation of breast cancer stem cells.
Karthik GM, Ma R, Lövrot J, Kis LL, Lindh C, Blomquist L, et al
Cancer Lett. 2015 Oct;367(1):76-87
Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.
Robertson S, Azizpour H, Smith K, Hartman J
Transl Res 2018 04;194():19-35