Next-Generation Pathology.

  title={Next-Generation Pathology.},
  author={Peter David Caie and David J. Harrison},
  journal={Methods in molecular biology},
The field of pathology is rapidly transforming from a semiquantitative and empirical science toward a big data discipline. Large data sets from across multiple omics fields may now be extracted from a patient's tissue sample. Tissue is, however, complex, heterogeneous, and prone to artifact. A reductionist view of tissue and disease progression, which does not take this complexity into account, may lead to single biomarkers failing in clinical trials. The integration of standardized multi-omics… 

Unusual structures inherent in point pattern data predict colon cancer patient survival

This work develops a point process methodology able to describe patterns in cell distribution within cancerous tissue samples and demonstrates that based solely on the spatial arrangement of cells it is able to predict patient survival.

Integrating molecular diagnostics into histopathology training: the Belfast model

This specialist training has two main goals: (1) to equip future practising histopathologists with basic knowledge of molecular diagnostics and (2) to create the option for those interested in a subspecialty experience in tissue molecular Diagnostics to pursue this training.

Progress and potential: training in genomic pathology.

The role of pathologists in genomic testing as well as current educational programs and future training needs in genomic pathology are reviewed for a future vital role in the evolving health care system and also the best possible patient care.

Whole-Section Tumor Micro-Architecture Analysis by a Two-Dimensional Phasor-Based Approach Applied to Polarization-Dependent Second Harmonic Imaging

It is shown that the “fibril entropy” parameter, which describes the tissue order on a selected spatial scale, is the most effective in enlightening the tumor edges, opening the possibility of their automatic segmentation.

Intuitive and interpretable visual communication of a complex statistical model of disease progression and risk

  • Jieyi LiOgnjen Arandjelovic
  • Computer Science
    2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
  • 2017
A software tool which focuses on the visualization of predictions made by a recently developed method which leverages data in the form of large scale electronic records for making diagnostic predictions, guided by risk predictions is described.

Bioinformatics Education in Pathology Training: Current Scope and Future Direction

Overall, pathology bioinformatics training can be incorporated into pathology resident curricula, provided there is motivation to incorporate, institutional support, educational resources, and adequate faculty expertise.

A brief glimpse of a tangled web in a small world: Tumor microenvironment

This mini review provides a brief guide on a range of factors to consider in the TME research.

Drug Screening Platforms and RPPA.

This chapter discusses and presents examples demonstrating how the latest advances in RPPA complement and integrate with other emerging drug screening platforms to support a new era of more informative and evidence-led drug discovery strategies.

Application of next generation sequencing to molecular diagnosis of inherited diseases.

This chapter reviews the up-to-date published application of next generation sequencing in clinical molecular diagnostic laboratories and emphasizes the various target gene enrichment methods and their advantages and shortcomings.

The current state of resident training in genomic pathology: a comprehensive analysis using the resident in-service examination.

The RISE is a powerful tool for assessing the state of resident training in genomic pathology and current results suggest a significant deficit, which provides a baseline to assess future initiatives to improve genomics education for pathology residents.



High-Content Phenotypic Profiling of Drug Response Signatures across Distinct Cancer Cells

The utility of a cell-based assay and custom designed image analysis algorithms designed to monitor morphologic phenotypic response in detail across distinct cancer cell types are shown and have the potential to drive the development of a new generation of novel therapeutic classes encompassing pharmacologic compositions or polypharmacology in appropriate disease context.

Predictive, personalized, preventive, participatory (P4) cancer medicine

One powerful approach to this challenge is the crowd-sourced recruitment of patients by bringing large clinical centers together with patient-advocate groups.

Modelling the spatial heterogeneity and molecular correlates of lymphocytic infiltration in triple-negative breast cancer

  • Yinyin Yuan
  • Biology, Medicine
    Journal of The Royal Society Interface
  • 2015
A quantitative measure of intratumour lymphocyte ratio is developed and found to be significantly associated with disease-specific survival in both TNBC cohorts independent to standard clinical parameters, and support the fusion of high-throughput image analysis and statistical modelling to offer reproducible and robust biomarkers for the objective identification of patients with poor prognosis and treatment options.

A Big Bang model of human colorectal tumor growth

A 'Big Bang' model is presented, whereby tumors grow predominantly as a single expansion producing numerous intermixed subclones that are not subject to stringent selection and where both public and most detectable private alterations arise early during growth.

Genetic and phenotypic diversity in breast tumor metastases.

The integrative method that couples ecologic models with experimental data in human tissue samples could be used for the improved prognostication of patients with cancer and for the design of more effective therapies for progressive disease.

Systems biology reveals new strategies for personalizing cancer medicine and confirms the role of PTEN in resistance to trastuzumab.

Quantitative PTEN protein expression was found to be the key determinant of resistance to anti-HER2 therapy in silico, which was predictive of unseen experiments in vitro using the PTEN inhibitor bp(V), further compelling evidence that PTEN, appropriately measured in the clinical setting, refines clinical decision making in patients treated with anti- HER2 therapies.

Stromal gene expression defines poor-prognosis subtypes in colorectal cancer

It is shown that the use of TGF-β signaling inhibitors to block the cross-talk between cancer cells and the microenvironment halts disease progression, and all poor-prognosis CRC subtypes share a gene program induced by T GF-β in tumor stromal cells.

Triple negative breast cancer: a multi-omics network discovery strategy for candidate targets and driving pathways.

The multi-omics molecular target and biomarker discovery approach presented here can offer ways forward on novel diagnostics and potentially help to design personalized therapeutics for TNBC in the future.

Towards the introduction of the ‘Immunoscore’ in the classification of malignant tumours

In colorectal cancer, the Immunoscore may add to the significance of the current AJCC/UICC TNM classification, since it has been demonstrated to be a prognostic factor superior to the AJCC or UICCTNM classification.

Genomic classifier ColoPrint predicts recurrence in stage II colorectal cancer patients more accurately than clinical factors.

BACKGROUND Approximately 20% of patients with stage II colorectal cancer will experience a relapse. Current clinical-pathologic stratification factors do not allow clear identification of these