Analytical strategies for identifying relevant phenotypes in microarray data

With microarray technology, the transcription thousands of genes can be determined simultaneously. The large number of genes, often assessed in a relatively small number of samples, presents a challenge. The risk of making false positive discoveries is substantial, and making biological sense of hundreds of identified genes is difficult. In response to this, a variety of methods for computerized analysis have been developed yet implementation of these is still fraught with challenges. This thesis focuses on the application of such methods in three areas of biomedical science, where the underlying biology needs more detailed characterization; cellular senescence, cell differentiation, and breast cancer.

Cellular senescence describes a state of growth arrest in vitro (cell cultures) believed to be of relevance for aging in mammals. In a comparison of seven microarray data sets addressing aging in human mouse and rat, and four data sets addressing cellular senescence in human and mouse, we discovered similarities between gene expression changes in the aging and senescence experiments, respectively. Resemblance between aging and cellular senescence could only be demonstrated between senescent cells and aging mice, not human. This finding indicates that aging in mice and humans can be substantially different, and that the cellular senescence process may not be a prominent feature of aging human tissues in vivo.

Adipogenesis requires exquisite control of cell-cycle proteins in two diverse types of adipocytes, brown and white. Brown adipose tissue, in contrast to white, can consume energy to generate heat. In a microarray experiment contrasting brown and white preadipocyte differentiation, we identified a novel transcriptional program in brown cells involving early expression of myogenic transcription factors previously thought to be unique to differentiation of muscle. We applied a novel array analysis strategy to understand which genes may be responsible for the brown adipocyte maturation and final unique cell phenotype. Our findings add a new dimension to current ideas on the developmental origin of brown adipose tissue.

In the last 40 years, survival in breast cancer patients has improved through the combined effects of earlier detection through mammography screening and adjuvant therapies. To achieve further progress, developing new prognostic markers, treatment predictive markers, and tailored therapy is important.

In two population based cohorts with 402 expression profiled primary breast cancers, we found that five proposed molecular subtypes of breast cancer could be collapsed to form two groups on the basis of gene expression in the long arm of chromosome 16, in agreement with histological grade.

We also explored the possibility to predict the sites of distant recurrences and found that lung and liver metastasis could be predicted. Prediction was characterized by poor sensitivity, numerous false positives, and strong dependence on biology underpinning histopathological grade and HER-2/neu status.

These findings indicate an important role for biology related to histopathological grade in breast cancer, and further investigation may provide means for better prognostication and treatment prediction.

List of scientific papers

I. Wennmalm K, Wahlestedt C, Larsson O. (2005). The expression signature of in vitro senescence resembles mouse but not human aging. Genome Biol. 6(13): R109
https://pubmed.ncbi.nlm.nih.gov/16420669

II. Timmons JA, Wennmalm K, Larsson O, Walden TB, Lassmann T, Petrovic N, Hamilton DL, Gimeno RE, Wahlestedt C, Baar K, Nedergaard J, Cannon B. (2007). Myogenic gene expression signature establishes that brown and white adipocytes originate from distinct cell lineages. Proc Natl Acad Sci USA. 104(11): 4401-6
https://pubmed.ncbi.nlm.nih.gov/17360536

III. Wennmalm K, Calza S, Ploner A, Hall P, Bjöhle J, Klaar S, Smeds J, Pawitan Y, Bergh J. (2007). Gene expression in 16q is associated with survival and differs between Sørlie breast cancer subtypes. Genes Chromosomes Cancer. 46(1): 87-97
https://pubmed.ncbi.nlm.nih.gov/17044045

IV. Wennmalm K, Bjöhle J, Smeds J, Klaar S, Ploner A, Bergh J. (1970). Prediction of distant metastasis site in primary breast cancers - results from two population derived cohorts. [Manuscript]