Halo image analysis platform

For quantification of proNGF staining, TMA slides were digitized at 200x absolute resolution using an Aperio AT2 scanner (Leica Biosystems, Victoria, Australia). Quantitative IHC analyses were performed using the Halo™ image analysis platform (Indica Labs, New Mexico, USA) under the supervision of a pathologist (MMW). The pixel intensities of DAB staining were calculated using the Area Quantification algorithm. Pixel intensity values were then used to determine the h-scores for each core (index calculated as the sum of 3 x % of pixels with strong staining + 2 x % of pixels with intermediate staining + 1 x % pixels with weak staining). To compare proNGF levels across the cohort, the h-scores were used to divide cases into 4 categories (0 = h-score <25, 1 = h-score 25-50, 2 = h-score 50-75, 3 = h-score >75).

Paraffin-embedded colon cancer patient specimens were obtained from the Biospecimen Procurement and Translational Pathology Shared Resource Facility of the Markey Cancer Center. The diagnosis and staging of each cancer case were confirmed by pathologist. IHC staining of paraffin-embedded tissue sections was performed as previously described^{8 (link),17 (link)}. The CPT1A antibody (#12252) was obtained from Cell Signaling. The stained sections were visualized using a Nikon Eclipse 80i upright microscope. To quantify the relative CPT1A expression levels, pixel intensity values were used to define the percentage of tumor cells with positive staining using the HALO image analysis platform (Indica Labs).

Quantification of staining intensities was performed as previously described^{34 (link)} using the Aperio AT2 scanner (Leica Biosystems, Victoria, Australia) and the Halo™ image analysis platform (Indica Labs, New Mexico, USA) under the supervision of a pathologist (MMW). Pixel intensity values were used to determine the h-scores for each core (index calculated as the sum of 3x% of pixels with strong staining +2x% of pixels with intermediate staining +1x% pixels with weak staining). Each core of the TMAs was investigated and the data were then submitted to statistical analysis.

High resolution-whole tissue scans were uploaded into HALO® Image Analysis Platform (Indica Labs) software for cell densitometry analysis. Whole tissue sections for all samples were spatially segmented within the software according to the different prostate lobes [88 (link)]. However, the dorsal-lateral prostate (DLP) lobes and the ventral prostate (VP) lobes were enlarged and, in all cases, fused to the anterior prostate (AP) lobes, making it challenging to differentiate the different prostate lobes accurately. Therefore, the tissue was segmented either as AP lobes or as VP + DLP lobes for cell densitometry analysis. Identification of the AP lobes was easy as the disease is mainly manifested in these lobes. Prostatic glands were excluded from the analysis due to the high autofluorescence.
Cell segmentation was performed based on DAPI counter-stain. Cells were counted within either the AP lobes or VP + DLP lobes according to four cell phenotypes: (i) DAPI⁺CD4⁺CD8^-B220^- (also referred as CD4⁺ cells); (ii) DAPI⁺CD4^-CD8⁺FOXP3^-B220^- (also referred as CD8⁺ cells); (iii) DAPI⁺ CD4⁺CD8^-FOXP3⁺B220^- (also referred as Tregs); and (iv) DAPI⁺CD4^-CD8^-FOXP3^-B220⁺ (also referred as B cells). The number of identified cells in each tissue zone was normalized to the total surface area to generate cell densities.