Multiplex Immunofluorescence in Formalin-Fixed Paraffin-Embedded Tumor Tissue to Identify Single-Cell–Level PI3K Pathway Activation

Abstract

Purpose: Identifying cancers with high PI3K pathway activity is critical for treatment selection and eligibility into clinical trials of PI3K inhibitors. Assessments of tumor signaling pathway activity need to consider intratumoral heterogeneity and multiple regulatory nodes. Experimental Design: We established a novel, mechanistically informed approach to assessing tumor signaling pathways by quantifying single-cell–level multiplex immunofluorescence using custom algorithms. In a proof-of-concept study, we stained archival formalin-fixed, paraffin-embedded (FFPE) tissue from patients with primary prostate cancer in two prospective cohort studies, the Health Professionals Follow-up Study and the Physicians’ Health Study. PTEN, stathmin, and phospho-S6 were quantified on 14 tissue microarrays as indicators of PI3K activation to derive cell-level PI3K scores. Results: In 1,001 men, 988,254 tumor cells were assessed (median, 743 per tumor; interquartile range, 290–1,377). PI3K scores were higher in tumors with PTEN loss scored by a pathologist, higher Gleason grade, and a new, validated bulk PI3K transcriptional signature. Unsupervised machine-learning approaches resulted in similar clustering. Within-tumor heterogeneity in cell-level PI3K scores was high. During long-term follow-up (median, 15.3 years), rates of progression to metastases and death from prostate cancer were twice as high in the highest quartile of PI3K activation compared with the lowest quartile (hazard ratio, 2.04; 95% confidence interval, 1.13–3.68). Conclusions: Our novel pathway-focused approach to quantifying single-cell–level immunofluorescence in FFPE tissue identifies prostate tumors with PI3K pathway activation that are more aggressive and may respond to pathway inhibitors.

A Personalized Genomics Approach of the Prostate Cancer

“…Alteration of TP53 (e.g., [ 66 ]) and another signaling (e.g., [ 67 ]) pathways in the prostate cancer were analyzed by several other groups before, but this is the first time after our knowledge that the analysis goes beyond expression regulation to explore also the expression coordination.…”

Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

“…For example, the same batches that showed higher-than-average biomarker values for stathmin also had higher-than-average values for PTEN. This example is noteworthy because both markers were assayed together on the same section of each TMA using multiplex immunofluorescence, and stathmin would be expected to be expressed in more aggressive tumors with activation of the PI3K signaling pathway while PTEN expression would be expected to be low in the same tumors ( Stopsack et al, 2020 ).…”

“…Immunostaining was generally performed separately for individual biomarkers yet always for all TMAs at the same time. Detailed immunohistochemistry staining and quantification procedures for each marker have been published (6,(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26) or are in preparation for estrogen receptor alpha (antibody SP1; Thermo Scientific, Waltham, MA) and an antibody (PPG5/10; Bio-Rad Laboratories, Hercules, CA) widely used to measure estrogen receptor beta.…”

Extent, impact, and mitigation of batch effects in tumor biomarker studies using tissue microarrays

“…For example, the same batches that showed higher-than-average biomarker values for stathmin also had higher-than-average values for PTEN. This example is noteworthy because both markers were assayed together on the same section of each TMA using multiplex immunofluorescence, and stathmin would be expected to be expressed in more aggressive tumors with activation of the PI3K signaling pathway while PTEN expression would be expected to be low in the same tumors (5).…”

“…Let ‫ݕ‬ ‫כ‬ indicate the batch effect-corrected biomarker level for tumor i on TMA j; ‫ݕ‬ , the uncorrected biomarker level for tumor i on TMA j; ‫ݕ‬ ො ఛୀ௫ , x th quantile of y for batch j (predicted value for y j from unadjusted quantile regression); ‫ݕ‬ ො ఛୀ௫,‫כ‬ is ‫ݕ‬ ො ఛୀ௫ with adjustment for confounders (predicted value for y j from adjusted quantile regression); and ‫ݕ‬ ത ఛୀ௫ , the x th quantile of y overall. Then the corrected biomarker level is 6) Quantile normalization. This approach assumes that samples on all batches, if not affected by batch effects, would not only have the same mean and variance but also the same distribution of individual biomarker values.…”