Exploring molecular links between lymph node invasion and cancer prognosis in human breast cancer

BackgroundLymph node invasion is one of the most powerful clinical factors in cancer prognosis. However, molecular level signatures of their correlation are remaining poorly understood. Here, we propose a new approach, monotonically expressed gene analysis (MEGA), to correlate transcriptional patterns of lymph node invasion related genes with clinical outcome of breast cancer patients.ResultsUsing MEGA, we scored all genes with their transcriptional patterns over progression levels of lymph node invasion from 278 non-metastatic breast cancer samples. Applied on 65 independent test data, our gene sets of top 20 scores (positive and negative correlations) showed significant associations with prognostic measures such as cancer metastasis, relapse and survival. Our method showed better accuracy than conventional two class comparison methods. We could also find that expression patterns of some genes are strongly associated with stage transition of pathological T and N at specific time. Additionally, some pathways including T-cell immune response and wound healing serum response are expected to be related with cancer progression from pathway enrichment and common motif binding site analyses of the inferred gene sets.ConclusionsBy applying MEGA, we can find possible molecular links between lymph node invasion and cancer prognosis in human breast cancer, supported by evidences of feasible gene expression patterns and significant results of meta-analysis tests.

[1]  Shridar Ganesan,et al.  X chromosomal abnormalities in basal-like human breast cancer. , 2006, Cancer cell.

[2]  Brad T. Sherman,et al.  DAVID: Database for Annotation, Visualization, and Integrated Discovery , 2003, Genome Biology.

[3]  Graziano Pesole,et al.  Pscan: finding over-represented transcription factor binding site motifs in sequences from co-regulated or co-expressed genes , 2009, Nucleic Acids Res..

[4]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[5]  A. Harris,et al.  Association of macrophage infiltration with angiogenesis and prognosis in invasive breast carcinoma. , 1996, Cancer research.

[6]  J. Massagué,et al.  Cancer Metastasis: Building a Framework , 2006, Cell.

[7]  R. Tibshirani,et al.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[8]  K J O'Byrne,et al.  The relationship between angiogenesis and the immune response in carcinogenesis and the progression of malignant disease. , 2000, European journal of cancer.

[9]  C. Bucana,et al.  Stat1 negatively regulates angiogenesis, tumorigenicity and metastasis of tumor cells , 2002, Oncogene.

[10]  J. Foekens,et al.  Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.

[11]  K. Alitalo,et al.  Metastasis: Lymphangiogenesis and cancer metastasis , 2002, Nature Reviews Cancer.

[12]  Crispin J. Miller,et al.  Simpleaffy: a BioConductor package for Affymetrix Quality Control and data analysis , 2005, Bioinform..

[13]  N. Weidner,et al.  Tumor microvessel density, p53 expression, tumor size, and peritumoral lymphatic vessel invasion are relevant prognostic markers in node-negative breast carcinoma. , 1994, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[14]  Israel Steinfeld,et al.  BMC Bioinformatics BioMed Central , 2008 .

[15]  R. Treisman,et al.  Characterization of SAP-1, a protein recruited by serum response factor to the c-fos serum response element , 1992, Cell.

[16]  R. Fisher Statistical methods for research workers , 1927, Protoplasma.

[17]  L. Coussens,et al.  Paradoxical roles of the immune system during cancer development , 2006, Nature Reviews Cancer.

[18]  J. Pollard Tumour-educated macrophages promote tumour progression and metastasis , 2004, Nature Reviews Cancer.

[19]  Van,et al.  A gene-expression signature as a predictor of survival in breast cancer. , 2002, The New England journal of medicine.

[20]  J. Massagué,et al.  Genetic determinants of cancer metastasis , 2007, Nature Reviews Genetics.

[21]  E. Lander,et al.  A molecular signature of metastasis in primary solid tumors , 2003, Nature Genetics.

[22]  Li Liu,et al.  Improved breast cancer prognosis through the combination of clinical and genetic markers , 2007, Bioinform..

[23]  R. Foster The biologic and clinical significance of lymphatic metastases in breast cancer. , 1996, Surgical oncology clinics of North America.

[24]  Wyeth W. Wasserman,et al.  A new generation of JASPAR, the open-access repository for transcription factor binding site profiles , 2005, Nucleic Acids Res..

[25]  L. Coussens,et al.  CD4(+) T cells regulate pulmonary metastasis of mammary carcinomas by enhancing protumor properties of macrophages. , 2009, Cancer cell.

[26]  Steve Horvath,et al.  Breast Cancer Molecular Signatures as Determined by SAGE: Correlation with Lymph Node Status , 2007, Molecular Cancer Research.

[27]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[28]  A. Lee,et al.  Occult axillary lymph node metastases in "node-negative" breast carcinoma. , 1993, Human pathology.

[29]  T. Barrette,et al.  ONCOMINE: a cancer microarray database and integrated data-mining platform. , 2004, Neoplasia.

[30]  J. Pollard,et al.  Tumor-associated macrophages press the angiogenic switch in breast cancer. , 2007, Cancer research.

[31]  Rainer Breitling,et al.  A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments , 2008, Bioinform..

[32]  Ash A. Alizadeh,et al.  Gene Expression Signature of Fibroblast Serum Response Predicts Human Cancer Progression: Similarities between Tumors and Wounds , 2004, PLoS biology.

[33]  I. Fidler,et al.  The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited , 2003, Nature Reviews Cancer.

[34]  Hua Yu,et al.  STATs in cancer inflammation and immunity: a leading role for STAT3 , 2009, Nature Reviews Cancer.

[35]  D. Tarin,et al.  Gene expression profiling of human lymph node metastases and matched primary breast carcinomas: Clinical implications , 2007, Molecular oncology.

[36]  E. Suchman,et al.  The American Soldier: Adjustment During Army Life. , 1949 .

[37]  M. Whitlock Combining probability from independent tests: the weighted Z‐method is superior to Fisher's approach , 2005, Journal of evolutionary biology.

[38]  Donald E. Henson,et al.  Relation of tumor size, lymph node status, and survival in 24,740 breast cancer cases , 1989 .

[39]  R. Weichselbaum,et al.  STAT1 Pathway Mediates Amplification of Metastatic Potential and Resistance to Therapy , 2009, PloS one.

[40]  W. L. McGuire,et al.  Prognostic factors for recurrence and survival in human breast cancer , 1987, Breast Cancer Research and Treatment.

[41]  D. Benbrook,et al.  Nature Reviews Cancer , 2003 .

[42]  K. Sugimachi,et al.  Local immune response to tumor invasion in esophageal squamous cell carcinoma: The expression of human leukocyte antigen‐DR and lymphocyte infiltration , 1994, Cancer.

[43]  C. Carter,et al.  Relation of tumor size, lymph node status, and survival in 24,740 breast cancer cases , 1989, Cancer.

[44]  Weiping Zou,et al.  Immunosuppressive networks in the tumour environment and their therapeutic relevance , 2005, Nature Reviews Cancer.

[45]  H. Dai,et al.  No common denominator for breast cancer lymph node metastasis , 2005, British Journal of Cancer.

[46]  S. Singletary,et al.  Breast Cancer Staging: Working With the Sixth Edition of the AJCC Cancer Staging Manual , 2006, CA: a cancer journal for clinicians.

[47]  D. Xie,et al.  Involvement of IFN regulatory factor (IRF)-1 and IRF-2 in the formation and progression of human esophageal cancers. , 2007, Cancer research.

[48]  W. Fuller,et al.  Distribution of the Estimators for Autoregressive Time Series with a Unit Root , 1979 .

[49]  Craig D. Shriver,et al.  A gene expression signature that defines breast cancer metastases , 2008, Clinical & Experimental Metastasis.

[50]  S G Hilsenbeck,et al.  Significance of axillary lymph node metastasis in primary breast cancer. , 1999, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[51]  Brad T. Sherman,et al.  Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources , 2008, Nature Protocols.