Spatial proteomic characterization of HER2-positive breast tumors through neoadjuvant therapy predicts response.

The addition of HER2-targeted agents to neoadjuvant chemotherapy has dramatically improved pathological complete response (pCR) rates in early-stage, HER2-positive breast cancer. Nonetheless, up to 50% of patients have residual disease after treatment, while others are likely overtreated. Here, we performed multiplex spatial proteomic characterization of 122 samples from 57 HER2-positive breast tumors from the neoadjuvant TRIO-US B07 clinical trial sampled pre-treatment, after 14-21 d of HER2-targeted therapy and at surgery. We demonstrated that proteomic changes after a single cycle of HER2-targeted therapy aids the identification of tumors that ultimately undergo pCR, outperforming pre-treatment measures or transcriptomic changes. We further developed and validated a classifier that robustly predicted pCR using a single marker, CD45, measured on treatment, and showed that CD45-positive cell counts measured via conventional immunohistochemistry perform comparably. These results demonstrate robust biomarkers that can be used to enable the stratification of sensitive tumors early during neoadjuvant HER2-targeted therapy, with implications for tailoring subsequent therapy.

Inter- and intra-tumor heterogeneity of metastatic prostate cancer determined by digital spatial gene expression profiling.

Metastatic prostate cancer (mPC) comprises a spectrum of diverse phenotypes. However, the extent of inter- and intra-tumor heterogeneity is not established. Here we use digital spatial profiling (DSP) technology to quantitate transcript and protein abundance in spatially-distinct regions of mPCs. By assessing multiple discrete areas across multiple metastases, we find a high level of intra-patient homogeneity with respect to tumor phenotype. However, there are notable exceptions including tumors comprised of regions with high and low androgen receptor (AR) and neuroendocrine activity. While the vast majority of metastases examined are devoid of significant inflammatory infiltrates and lack PD1, PD-L1 and CTLA4, the B7-H3/CD276 immune checkpoint protein is highly expressed, particularly in mPCs with high AR activity. Our results demonstrate the utility of DSP for accurately classifying tumor phenotype, assessing tumor heterogeneity, and identifying aspects of tumor biology involving the immunological composition of metastases.

Multiplex digital spatial profiling of proteins and RNA in fixed tissue.

Digital Spatial Profiling (DSP) is a method for highly multiplex spatial profiling of proteins or RNAs suitable for use on formalin-fixed, paraffin-embedded (FFPE) samples. The approach relies on (1) multiplexed readout of proteins or RNAs using oligonucleotide tags; (2) oligonucleotide tags attached to affinity reagents (antibodies or RNA probes) through a photocleavable (PC) linker; and (3) photocleaving light projected onto the tissue sample to release PC oligonucleotides in any spatial pattern across a region of interest (ROI) covering 1 to ~5,000 cells. DSP is capable of single-cell sensitivity within an ROI using the antibody readout, with RNA detection feasible down to ~600 individual mRNA transcripts. We show spatial profiling of up to 44 proteins and 96 genes (928 RNA probes) in lymphoid, colorectal tumor and autoimmune tissues by using the nCounter system and 1,412 genes (4,998 RNA probes) by using next-generation sequencing (NGS). DSP may be used to profile not only proteins and RNAs in biobanked samples but also immune markers in patient samples, with potential prognostic and predictive potential for clinical decision-making.