Quantitative stain-free imaging and digital profiling of collagen structure reveal diverse survival of triple negative breast cancer patients.

BACKGROUND: Stromal and collagen biology has a significant impact on tumorigenesis and metastasis. Collagen is a major structural extracellular matrix component in breast cancer, but its role in cancer progression is the subject of historical debate. Collagen may represent a protective layer that prevents cancer cell migration, while increased stromal collagen has been demonstrated to facilitate breast cancer metastasis. METHODS: Stromal remodeling is characterized by collagen fiber restructuring and realignment in stromal and tumoral areas. The patients in our study were diagnosed with triple-negative breast cancer in Singapore General Hospital from 2003 to 2015. We designed novel image processing and quantification pipelines to profile collagen structures using numerical imaging parameters. Our solution differentiated the collagen into two distinct modes: aggregated thick collagen (ATC) and dispersed thin collagen (DTC). RESULTS: Extracted parameters were significantly associated with bigger tumor size and DCIS association. Of numerical parameters, ATC collagen fiber density (CFD) and DTC collagen fiber length (CFL) were of significant prognostic value for disease-free survival and overall survival for the TNBC patient cohort. Using these two parameters, we built a predictive model to stratify the patients into four groups. CONCLUSIONS: Our study provides a novel insight for the quantitation of collagen in the tumor microenvironment and will help predict clinical outcomes for TNBC patients. The identified collagen parameters, ATC CFD and DTC CFL, represent a new direction for clinical prognosis and precision medicine. We also compared our result with benign samples and DICS samples to get novel insight about the TNBC heterogeneity. The improved understanding of collagen compartment of TNBC may provide insights into novel targets for better patient stratification and treatment.

Quantification of gastrointestinal sodium channelopathy.

Na(v)1.5 sodium channels, encoded by SCN5A, have been identified in human gastrointestinal interstitial cells of Cajal (ICC) and smooth muscle cells (SMC). A recent study found a novel, rare missense R76C mutation of the sodium channel interacting protein telethonin in a patient with primary intestinal pseudo-obstruction. The presence of a mutation in a patient with a motility disorder, however, does not automatically imply a cause-effect relationship between the two. Patch clamp experiments on HEK-293 cells previously established that the R76C mutation altered Na(v)1.5 channel function. Here the process through which these data were quantified to create stationary Markov state models of wild-type and R76C channel function is described. The resulting channel descriptions were included in whole cell ICC and SMC computational models and simulations were performed to assess the cellular effects of the R76C mutation. The simulated ICC slow wave was decreased in duration and the resting membrane potential in the SMC was depolarized. Thus, the R76C mutation was sufficient to alter ICC and SMC cell electrophysiology. However, the cause-effect relationship between R76C and intestinal pseudo-obstruction remains an open question.

An extended bidomain framework incorporating multiple cell types.

The muscular layers within the walls of the gastrointestinal tract contain two distinct cell types, the interstitial cells of Cajal and smooth muscle cells, which together produce rhythmic depolarizations known as slow waves. The bidomain model of tissue-level electrical activity consists of single intracellular and extracellular domains separated by an intervening membrane at all points in space and is therefore unable to adequately describe the presence of two distinct cell types in its conventional form. Here, an extension to the bidomain framework is presented whereby multiple interconnected cell types can be incorporated. Although the derivation is focused on the interactions of the interstitial cells of Cajal and smooth muscle cells, the conceptual framework can be more generally applied. Simulations demonstrating the feasibility of the proposed model are also presented.

Multiplex immunohistochemistry/immunofluorescence (mIHC/IF) for PD-L1 testing in triple-negative breast cancer: a translational assay compared with conventional IHC.

BACKGROUND: Programmed death-ligand 1 (PD-L1) monoclonal antibody therapy has recently gained approval for treating metastatic triple-negative breast cancer (TNBC) -, in particular in the PD-L1+ patient subgroup of the recent IMpassion130 trial. The SP142 PD-L1 antibody clone was used as a predictive assay in this trial, but this clone was found to be an outlier in previous harmonisation studies in lung cancer. AIMS: To address the comparability of PD-L1 clones in TNBC, we evaluated the concordance between conventional immunohistochemistry (IHC) and multiplex immunohistochemistry/immunofluorescence (mIHC/IF) that allowed simultaneous quantification of three different PD-L1 antibodies (22C3, SP142 and SP263). METHODS: Our cohort comprised 25 TNBC cases, 12 non-small-cell lung carcinomas and 8 other cancers. EpCAM labelling was used to distinguish tumour cells from immune cells. RESULTS: Moderate-to-strong correlations in PD-L1 positivity were found between results obtained through mIHC/IF and IHC. Individual concordance rates in the study ranged from 67% to 100%, with Spearman's rank correlation coefficient values up to 0.88. CONCLUSIONS: mIHC/IF represents a promising tool in the era of cancer immunotherapy, as it can simultaneously detect and quantify PD-L1 labelling with multiple antibody clones, and allow accurate evaluation of tumour and immune cells. Clinicians and pathologists require this information to predict patient response to anti-PD-1/PD-L1 therapy. The adoption of this assay may represent a significant advance in the management of therapeutically challenging cancers. Further analysis and assay harmonisation are essential for translation to a routine diagnostic setting.

A quantitative model of human jejunal smooth muscle cell electrophysiology.

Recently, a number of ion channel mutations have been identified in the smooth muscle cells of the human jejunum. Although these are potentially significant in understanding diseases that are currently of unknown etiology, no suitable computational cell model exists to evaluate the effects of such mutations. Here, therefore, a biophysically based single cell model of human jejunal smooth muscle electrophysiology is presented. The resulting cellular description is able to reproduce experimentally recorded slow wave activity and produces realistic responses to a number of perturbations, providing a solid platform on which the causes of intestinal myopathies can be investigated.

A computational approach to understanding gastrointestinal motility in health and disease.

Gastrointestinal (GI) motility disorders are not well understood, resulting in patient management that typically controls symptoms. Patients suffer from reduced quality of life and incur large costs from chronic GI disorders. It is imperative to elucidate underlying mechanisms causing GI motility disorders that, in turn, can facilitate development of treatment such as drug therapeutics. To this end, we seek to use multi-scale computational models to better understand GI motility in health and disease. An initial computational framework was established to study genetic perturbation in causing a phenotypical change at the GI tissue level. Computer models describing a couple of genetic perturbations were developed and examined in the multi-scale framework. Preliminary findings suggest alterations to phenotype that may adversely affect GI motility. However, much work remains, given the tissue complexity and uncertainties in our knowledge of the GI organs. A future direction will be to incorporate multi-scale mechanical models in the current framework.

A preliminary model of gastrointestinal electromechanical coupling.

Gastrointestinal (GI) motility is coordinated by several cooperating mechanisms, including electrical slow wave activity, the enteric nervous system (ENS), and other factors. Slow waves generated in interstitial cells of Cajal (ICC) depolarize smooth muscle cells (SMC), generating basic GI contractions. This unique electrical coupling presents an added layer of complexity to GI electromechanical models, and a current barrier to further progress is the lack of a framework for ICC-SMC-contraction coupling. In this study, an initial framework for the electromechanical coupling was developed in a 2-D model. At each solution step, the slow wave propagation was solved first and [Ca(2+)](i) in the SMC model was related to a Ca(2+)-tension-extension relationship to simulate active contraction. With identification of more GI-specific constitutive laws and material parameters, the ICC-SMC-contraction approach may underpin future GI electromechanical models of health and disease states.

A model of slow wave propagation and entrainment along the stomach.

Interstitial cells of Cajal (ICC) isolated from different regions of the stomach generate spontaneous electrical slow wave activity at different frequencies, with cells from the proximal stomach pacing faster than their distal counterparts. However, in vivo there exists a uniform pacing frequency; slow waves propagate aborally from the proximal stomach and subsequently entrain distal tissues. Significant resting membrane potential (RMP) gradients also exist within the stomach whereby membrane polarization generally increases from the fundus to the antrum. Both of these factors play a major role in the macroscopic electrical behavior of the stomach and as such, any tissue or organ level model of gastric electrophysiology should ensure that these phenomena are properly described. This study details a dual-cable model of gastric electrical activity that incorporates biophysically detailed single-cell models of the two predominant cell types, the ICC and smooth muscle cells. Mechanisms for the entrainment of the intrinsic pacing frequency gradient and for the establishment of the RMP gradient are presented. The resulting construct is able to reproduce experimentally recorded slow wave activity and provides a platform on which our understanding of gastric electrical activity can advance.