In anatomic pathology, immunohistochemistry (IHC) serves as a diagnostic and prognostic method for identification of disease markers in tissue samples that directly influences classification and grading the disease, influencing patient management. However, till today over most of the world, pathological analysis of tissue samples remained a time-consuming and subjective procedure, wherein the intensity of antibody staining is manually judged and thus scoring decision is directly influenced by visual bias. This instigated us to design a simple method of automated digital IHC image analysis algorithm for an unbiased, quantitative assessment of antibody staining intensity in tissue sections. As a first step, we adopted the spectral deconvolution method of DAB/hematoxylin color spectra by using optimized optical density vectors of the color deconvolution plugin for proper separation of the DAB color spectra. Then the DAB stained image is displayed in a new window wherein it undergoes pixel-by-pixel analysis, and displays the full profile along with its scoring decision. Based on the mathematical formula conceptualized, the algorithm is thoroughly tested by analyzing scores assigned to thousands (n = 1703) of DAB stained IHC images including sample images taken from human protein atlas web resource. The IHC Profiler plugin developed is compatible with the open resource digital image analysis software, ImageJ, which creates a pixel-by-pixel analysis profile of a digital IHC image and further assigns a score in a four tier system. A comparison study between manual pathological analysis and IHC Profiler resolved in a match of 88.6% (P<0.0001, CI = 95%). This new tool developed for clinical histopathological sample analysis can be adopted globally for scoring most protein targets where the marker protein expression is of cytoplasmic and/or nuclear type. We foresee that this method will minimize the problem of inter-observer variations across labs and further help in worldwide patient stratification potentially benefitting various multinational clinical trial initiatives.

Human sodium iodide symporter (hNIS) gene over-expression is under active consideration worldwide as an alternative target molecule for breast cancer (BC) diagnosis and targeted radio-iodine treatment. However, the field demands better stratified analysis of endogenous hNIS expression across major BC subtypes. Therefore, we have analyzed subtype-specific variation of hNIS overexpression in breast tumor tissue samples by immunohistochemistry (IHC) and also report the development of a homogeneous, quantitative analysis method of digital IHC images. hNIS expression was analyzed from 108 BC tissue samples by IHC. Sub-cellular localization of hNIS protein was analyzed by dual immunofluorescence (IF) staining method using hNIS and HER2 antibodies. An ImageJ based two-step digital analysis method was developed and applied for the bias-free analysis of the images. Staining of the tumor samples show 70% cases are hNIS positive indicating high incidence of hNIS positive cases in BC. More importantly, a subtype specific analysis done for the first time shows that hNIS expression is overly dominated in estrogen receptor (ER) positive cases than the receptor negative cases. Further, 56% of the ER+ve, PgR+ve, HER2-ve and 36% of ER+ve, PgR+ve, HER2+ve cases show highest intensity staining equivalent to the thyroid tissue. A significant positive correlation is also observed between hNIS and estrogen receptor expression (p = 0.0033, CI = 95%) suggesting hNIS mediated targeted radio-iodine therapy procedures may benefit both ER+ve, PgR+ve, HER2–ve as well as HER2+ve cases. Further, in a few cases, hNIS and HER2 protein localization is demonstrated by overlapping membrane co-expression. ImageJ based image analysis method shows over 70% match with manual pathological scoring method. The study indicates a positive link between hNIS and ER expression in BC. The quantitative IHC image analysis method reported here will further help in patient stratification and potentially benefit global clinical assessment where hNIS mediated targeted ¹³¹I radio-ablative therapy is aimed.

The unresolved and paramount challenge in bio-imaging and targeted therapy is to clearly define and demarcate the physical margins of tumor tissue. The ability to outline the healthy vital tissues to be carefully navigated with transection while an intraoperative surgery procedure is performed sets up a necessary and under-researched goal. To achieve the aforementioned objectives, there is a need to optimize design considerations in order to not only obtain an effective imaging agent but to also achieve attributes like favorable water solubility, biocompatibility, high molecular brightness, and a tissue specific targeting approach. The emergence of near infra-red fluorescence (NIRF) light for tissue scale imaging owes to the provision of highly specific images of the target organ. The special characteristics of near infra-red window such as minimal auto-fluorescence, low light scattering, and absorption of biomolecules in tissue converge to form an attractive modality for cancer imaging. Imparting molecular fluorescence as an exogenous contrast agent is the most beneficial attribute of NIRF light as a clinical imaging technology. Additionally, many such agents also display therapeutic potentials as photo-thermal agents, thus meeting the dual purpose of imaging and therapy. Here, we primarily discuss molecular imaging and therapeutic potentials of two such classes of materials, i.e., inorganic NIR dyes and metallic gold nanoparticle based materials.

Development of bioluminescence resonance energy transfer (BRET) based genetic sensors for sensing biological functions such as protein–protein interactions (PPIs) in vivo has a special value in measuring such dynamic events at their native environment. Since its inception in the late nineties, BRET related research has gained significant momentum in terms of adding versatility to the assay format and wider applicability where it has been suitably used. Beyond the scope of quantitative measurement of PPIs and protein dimerization, molecular imaging applications based on BRET assays have broadened its scope for screening pharmacologically important compounds by in vivo imaging as well. In this mini-review we focus on an in-depth analysis of engineered BRET systems developed and their successful application to cell-based assays as well as in vivo non-invasive imaging in live subjects.

Since its first documentation, breast cancer (BC) has been a conundrum that ails millions of women every year. This cancer has been well studied by researchers all over the world, which has improved the patient outcome significantly. There are many diagnostic markers to identify the disease, but early detection and then subclassification of this cancer remain dubious. Even after the correct diagnosis, more than half the patients come back with a more aggressive and metastatic tumor. The underpinning mechanism that governs the resistance includes over-amplification of receptors, mutations in key gene targets, and activation of different signaling. A plethora of drugs have been devised that have shown promising results in clinical settings. However, in recent times, the role played by cancer stem cells in disease progression and their interaction in mediating the resistance to cellular insults have come into the limelight. As breast cancer stem cells (BCSCs) are dormant in nature, it is highly likely that they fail to directly respond to the cytotoxic drugs which are meant for ablating rapidly proliferating cells. Furthermore, the absence of well-characterized, drug-able surface markers to date, has limited the application of targeted therapies in complete eradication of the disease. In this review, our intent is to discuss versatile therapeutics in practice followed by discussing the upcoming therapy strategies in the pipeline for BC. Furthermore, we focus on the roles played by BCSCs in mediating the resistance, and therefore, the aspects of new therapeutics against BCSCs under development that may ease the burden in future has also been discussed.