Microarrays and Epidemiology: Ensuring the Impact and Accessibility of Research Findings

Troester, Melissa A.; Millikan, Robert C.; Perou, Charles M.

doi:10.1158/1055-9965.epi-08-0867

Cited by 11 publications

(8 citation statements)

References 22 publications

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“…Our analyses of cocultures show that this wound response signaling is up-regulated in this model system, with both Basal-like and Luminal cocultures showing altered expression of genes in the 200-probe/130 gene wound response signature. However, consistent with our previous observations in vivo (33), in coculture different genes appeared to be upregulated in each cancer subtype with CCL2, CSF3, CXCL1, LAMC2 TLR2, TNFRSF6B and TREM1 up-regulated in Basal-likes and CEACAM6, RECK, S100A8 and TMC5 up-regulated in Luminals. Relative to monocultures comparing Basal-like and Luminal cancer cells, cocultures produced a broader range of expression differences.…”

Section: Resultssupporting

confidence: 91%

Interactions with Fibroblasts Are Distinct in Basal-Like and Luminal Breast Cancers

Camp

Elloumi

Roman-Perez

et al. 2011

Molecular Cancer Research

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116

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Basal-like breast cancers have several well-characterized distinguishing molecular features, but most of these are features of the cancer cells themselves. The unique stromal-epithelial interactions, and more generally, microenvironmental features of basal-like breast cancers have not been well characterized. To identify characteristic microenvironment features of basal-like breast cancer, we performed cocultures of several basal-like breast cancer cell lines with fibroblasts and compared these with cocultures of luminal breast cancer cell lines with fibroblasts. Interactions between basal-like cancer cells and fibroblasts induced expression of numerous interleukins and chemokines, including IL-6, IL-8, CXCL1, CXCL3, and TGFb. Under the influence of fibroblasts, basal-like breast cancer cell lines also showed increased migration in vitro. Migration was less pronounced for luminal lines; but, these lines were more likely to have altered proliferation. These differences were relevant to tumor biology in vivo, as the gene set that distinguished luminal and basal-like stromal interactions in coculture also distinguishes basal-like from luminal tumors with 98% accuracy in 10-fold cross-validation and 100% accuracy in an independent test set. However, comparisons between cocultures where cells were in direct contact and cocultures where interaction was solely through soluble factors suggest that there is an important impact of direct cell-to-cell contact. The phenotypes and gene expression changes invoked by cancer cell interactions with fibroblasts support the microenvironment and cell-cell interactions as intrinsic features of breast cancer subtypes. Mol Cancer Res; 9(1); 3-13. Ó2010 AACR.

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Section: Resultssupporting

confidence: 91%

Interactions with Fibroblasts Are Distinct in Basal-Like and Luminal Breast Cancers

Camp

Elloumi

Roman-Perez

et al. 2011

Molecular Cancer Research

Self Cite

116

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“…It is interesting to note that the subsequent incidence of metachronous prostate cancer seems to be reduced by radiation used in the treatment of rectal cancer 48,49 . This decreased risk of prostate cancer in men who have received radiation therapy for rectal cancer may be related to the curative effect on occult prostate cancer.…”

Section: Longer Term Effects Of Radiotherapy and Patient Follow-upmentioning

confidence: 99%

Interactions in the aetiology, presentation and management of synchronous and metachronous adenocarcinoma of the prostate and rectum

Nash

Turner

Hickish

et al. 2012

annals

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Adenocarcinoma of the prostate and rectum are common male pelvic cancers and may present synchronously or metachronously and, due to their anatomic proximity. The treatment of rectal or prostate cancer (in particular surgery and/or radiotherapy) may alter the presentation, incidence and management should a metachronous tumour develop. This review focuses on the interaction between prostatic and rectal cancer diagnosis and management. We have restricted the scope of this large topic to general considerations, management of rectal cancer after prostate cancer treatment and vice versa, management of synchronous disease and cancer follow-up issues.

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“…For example, the term sample may bear a completely different meaning to a statistician and a biologist. While such a misunderstanding can be easily detected and resolved, problems arising from other terms may be more difficult to spot: test set versus validation set, supervised versus unsupervised, and so forth, [56].…”

Section: Development Of Standardsmentioning

confidence: 99%

“…However, in general, standards for computational and statistical models do not seem to be widely embraced yet, at least life science publications do not widely adhere to these standards, arguably because they are not enforced by journals and other publication sources-yet. There are many critical voices, though, calling for standards implementing good statistical guidelines [56]. It can be speculated that in the near future journals will begin enforcing standardized reports of computational models, similarly to the MIAME standard for microarray data.…”

Section: Development Of Standardsmentioning

confidence: 99%

Quo Vadis, Artificial Intelligence?

Berrar

Sato

Schuster

2010

Advances in Artificial Intelligence

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Since its conception in the mid 1950s, artificial intelligence with its great ambition to understand and emulate intelligence in natural and artificial environments alike is now a truly multidisciplinary field that reaches out and is inspired by a great diversity of other fields. Rapid advances in research and technology in various fields have created environments into which artificial intelligence could embed itself naturally and comfortably. Neuroscience with its desire to understand nervous systems of biological organisms and systems biology with its longing to comprehend, holistically, the multitude of complex interactions in biological systems are two such fields. They target ideals artificial intelligence has dreamt about for a long time including the computer simulation of an entire biological brain or the creation of new life forms from manipulations of cellular and genetic information in the laboratory. The scope for artificial intelligence in neuroscience and systems biology is extremely wide. This article investigates the standing of artificial intelligence in relation to neuroscience and systems biology and provides an outlook at new and exciting challenges for artificial intelligence in these fields. These challenges include, but are not necessarily limited to, the ability to learn from other projects and to be inventive, to understand the potential and exploit novel computing paradigms and environments, to specify and adhere to stringent standards and robust statistical frameworks, to be integrative, and to embrace openness principles.

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Microarrays and Epidemiology: Ensuring the Impact and Accessibility of Research Findings

Cited by 11 publications

References 22 publications

Interactions with Fibroblasts Are Distinct in Basal-Like and Luminal Breast Cancers

Interactions with Fibroblasts Are Distinct in Basal-Like and Luminal Breast Cancers

Interactions in the aetiology, presentation and management of synchronous and metachronous adenocarcinoma of the prostate and rectum

Quo Vadis, Artificial Intelligence?

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