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Professor Sunil Lakhani

24 June 2008

Molecular classification of breast Ca not definite

Making absolute assumptions based on molecular classification of breast cancer will not help patient management, says an eminent molecular pathologist.

“There is an impression that all the molecular technologies we have today gives us information that is absolute … [either] black or white,” said Professor Sunil Lakhani, head of molecular and cellular pathology at the school of medicine, University of Queensland, Australia.

He said if pathologists believe in this assumption, creativity will be lost when using the technology to manage patients. He emphasized that molecular classification is “evolving and exciting”,
but still not ready to be used in clinical practice.

Breast cancers are generally classified by morphology as benign or malignant; in situ or invasive; luminal or basal; and, primary or secondary. These classifications are not just academic, as they are used for prognosis and prediction of disease progression.

But morphological features of breast cancers are often difficult to distinguish from one another, a well-known limitation in pathology. And as molecular pathology is often ‘anchored’ upon morphological analysis ie,molecular signatures are compared with morphological features, this limitation affects molecular classification.

Current molecular techniques are also unable to differentiate between some lesions due to
their inherent biology eg, differences between benign and malignant invasive carcinomas are quantitative, not qualitative.

And just as we understand the limitations in grading by conventional pathology, said Lakhani, we should realize the same is true with molecular technology.

“Although we know in conventional situations that a grade two tumor may turn into a grade
three tumor when assessed by another pathologist due to an element of subjectivity, the same is also true for molecular signatures.”

A Type A molecular signature could be classified as Type B by another laboratory, largely due to the different platforms or statistical packages used. This points to a lack of validation of technology and platforms, he said.

Other areas of caution in breast cancer molecular classification include the use of small or inappropriate types of samples, which could eventually lead to biasness in analysis.

Despite his warnings for caution in data interpretation, Lakhani said expression profiling
is providing more information about patient prognosis than can be gauged from pathological examination of tissues.

He is also optimistic about its use in the future. “I’ve no doubt, over the next five to 10 years, that a huge amount of information will help us to better predict responses to chemotherapy, and in stratifying patients differently.”


Sunil R. Lakhani is Professor and Head of Molecular & Cellular Pathology in The School of Medicine, University of Queensland. He is Head of the Molecular Pathology Laboratory and Principal Research Fellow at the Queensland Institute of Medical Research (QIMR) and Visiting Breast Pathology Specialist at The Royal Brisbane and Women's Hospital. Prior to his move to Australia in 2004, he was Professor of Pathology at The Institute of Cancer Research and The Royal Marsden Hospital, London, UK. His current research interests include lobular carcinoma and its variants, genomic profiles on normal breast epithelial and stem cells, molecular genetics of tumours with a basal phenotype and molecular pathology of familial breast cancers. He
has authored/edited 5 undergraduate & postgraduate textbooks in pathology and published 150 scientific papers. He is a series editor for the WHO Classification Books and on the panel for the WHO Classification of Tumours of the Breast.

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