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Multispectral remote sensing data is available with broad spectral bands in the wavelength range of Visible-NIR-SWIR, and finds its applications in assessment of Land Use Land Cover classes (LULC). There are plenty of onboard sensors which are providing these datasets regularly. However, for detailed LULC classification there is a requirement of distinguishing spectrally similar land cover features, which is possible through hyperspectral data. These datasets are spectrally rich and are available with narrow spectral bandwidth but the availability of such datasets is limited. This is due to requirement of sophisticated detectors and high storage, which makes the acquisition of these datasets challenging. Therefore, there is a opportunity to utilize the available multispectral data for generating hyperspectral data. Existing spectral reconstruction technique is used for simulating hyperspectral bands from multispectral bands in combination with ground spectra. In this study, an attempt has been made to develop a software solution for automating the simulation of hyperspectral data using multispectral data in an open source platform. The developed software solution (HyDAS) consists of modules for satellite data visualization, spectral library creation, spectral unmixing and hyperspectral data simulation. HyDAS toolbox is successfully tested for simulating hyperspectral data from EO-1 ALI multispectral data. The simulated results were validated using the available EO-1 Hyperion data and results were satisfactory with similarity being 80–90%. This open source solution was also tested for simulating hyperspectral bands from EO-1 ALI and Indian Satellite (LISS III & LISS IV) multispectral datasets, the results obtained were satisfactory for species level classification

Purpose To evaluate the feasibility of syngeneic mouse models of breast cancer by analyzing the efficacy of immune checkpoint inhibitors (ICIs) and potential predictive biomarkers. Methods Four syngeneic mouse models of triple-negative breast cancer (TNBC) JC, 4T1, EMT6 and E0771 cells were injected subcutaneously. When the tumor reached 50–100 mm3, each mouse model was divided into treatment (murine PD-1 antibody) and no-treatment control. Treatment group is further divided into the responder and nonresponder groups. Potential predictive biomarkers were evaluated by analyzing serum cytokines, peripheral blood T cells and tumor infiltrating immune cells. Results The JC model showed the highest tumor response rate (40%, 4/10) of syngeneic models: 4T1 (36%, 4/11), EMT6 (36%, 4/11), or E0771 model (23%, 3/13). Early change of tumor size at 7 days post PD-1 inhibitor treatment predicted the final efficacy of PD-1 inhibitor. Peripheral blood CD8 + and CD4 + T cells with or without Ki67 expression at 7 days post-PD-1 inhibitor treatment were higher in the finally designated responder group than in the nonresponder group. At the time of sacrifice, analyses of tumor infiltrating lymphocytes consistently supported these results. Furthermore, serum IFN-γ at 7 days post-PD-1 inhibitor treatment was also higher in responders than in nonresponders, suggesting that early changes of these markers could be predictive biomarkers of the final efficacy of ICIs. Conclusions Our syngeneic mouse model of TNBC is a feasible preclinical platform to evaluate ICI efficacies combined with other drugs and predictive biomarkers in the screening period of immune-oncology drug development.

Background: Recently, cyclin-dependent kinase (CDK) 4/6 inhibitors have been widely used to treat advanced hormone receptor-positive breast cancer. Despite promising clinical outcomes, almost all patients eventually acquire resistance to CDK4/6 inhibitors. Hence, understanding the mechanisms of acquired resistance to CDK4/6 inhibitors is crucial for developing alternative treatment strategies. Therefore, the present study screened genes associated with palbociclib resistance through genomics and transcriptomics in preclinical breast cancer models. Methods: Palbociclib-resistant cells, MCF7-PR and T47D-PR, were generated by exposing MCF7 and T47D cells to palbociclib. After confirming acquired resistance through in vitro assays, whole-exome sequencing (WES) and mRNA microarray were performed to compare the genomic and transcriptomic landscape between palbociclib-sensitive and resistant cells. Real time-PCR was performed to confirm differentially expressed genes.Results: Microarray analysis comparing MCF7 and MCF7-PR cells revealed 651 differentially expressed genes (DEGs) (fold change >2 or Conclusions: Palbociclib resistance was found to be associated with deregulated immune pathway in preclinical breast cancer models. Further studies are warranted to evaluate whether immune pathways may be a therapeutic target to overcome CDK4/6 inhibitor resistance.