A pan-cancer patient-derived xenograft histology image repository with genomic and pathologic annotations enables deep learning analysis

Patient-derived xenografts (PDX) model human intra- and intertumoral heterogeneity in the context of the intact tissue of immunocompromised mice. Histologic imaging via hematoxylin and eosin (H&E) staining is routinely performed on PDX samples, which could be harnessed for computational analysis. Prior studies of large clinical H&E image repositories have shown that deep learning analysis can identify intercellular and morphologic signals correlated with disease phenotype and therapeutic response. In this study, we developed an extensive, pan-cancer repository of \u3e1,000 PDX and paired parental tumor H&E images. These images, curated from the PDX Development and Trial Centers Research Network Consortium, had a range of associated genomic and transcriptomic data, clinical metadata, pathologic assessments of cell composition, and, in several cases, detailed pathologic annotations of neoplastic, stromal, and necrotic regions. The amenability of these images to deep learning was highlighted through three applications: (i) development of a classifier for neoplastic, stromal, and necrotic regions; (ii) development of a predictor of xenograft-transplant lymphoproliferative disorder; and (iii) application of a published predictor of microsatellite instability. Together, this PDX Development and Trial Centers Research Network image repository provides a valuable resource for controlled digital pathology analysis, both for the evaluation of technical issues and for the development of computational image-based methods that make clinical predictions based on PDX treatment studies. Significance: A pan-cancer repository of \u3e1,000 patient-derived xenograft hematoxylin and eosin-stained images will facilitate cancer biology investigations through histopathologic analysis and contributes important model system data that expand existing human histology repositories

QuantFusion: Novel Unified Methodology for Enhanced Coverage and Precision in Quantifying Global Proteomic Changes in Whole Tissues

Single quantitative platforms such as label-based or label-free quantitation (LFQ) present compromises in accuracy, precision, protein sequence coverage, and speed of quantifiable proteomic measurements. To maximize the quantitative precision and the number of quantifiable proteins or the quantifiable coverage of tissue proteomes, we have developed a unified approach, termed QuantFusion, that combines the quantitative ratios of all peptides measured by both LFQ and label-based methodologies. Here, we demonstrate the use of QuantFusion in determining the proteins differentially expressed in a pair of patient-derived tumor xenografts (PDXs) representing two major breast cancer (BC) subtypes, basal and luminal. Label-based in-spectra quantitative peptides derived from amino acid-coded tagging (AACT, also known as SILAC) of a non-malignant mammary cell line were uniformly added to each xenograft with a constant predefined ratio, from which Ratio-of-Ratio estimates were obtained for the label-free peptides paired with AACT peptides in each PDX tumor. A mixed model statistical analysis was used to determine global differential protein expression by combining complementary quantifiable peptide ratios measured by LFQ and Ratio-of-Ratios, respectively. With minimum number of replicates required for obtaining the statistically significant ratios, QuantFusion uses the distinct mechanisms to “rescue” the missing data inherent to both LFQ and label-based quantitation. Combined quantifiable peptide data from both quantitative schemes increased the overall number of peptide level measurements and protein level estimates. In our analysis of the PDX tumor proteomes, QuantFusion increased the number of distinct peptide ratios by 65%, representing differentially expressed proteins between the BC subtypes. This quantifiable coverage improvement, in turn, not only increased the number of measurable protein fold-changes by 8% but also increased the average precision of quantitative estimates by 181% so that some BC subtypically expressed proteins were rescued by QuantFusion. Thus, incorporating data from multiple quantitative approaches while accounting for measurement variability at both the peptide and global protein levels make QuantFusion unique for obtaining increased coverage and quantitative precision for tissue proteomes

A randomized phase 2 study of neoadjuvant carboplatin and paclitaxel with or without atezolizumab in triple negative breast cancer (TNBC) - NCI 10013

Atezolizumab with chemotherapy has shown improved progression-free and overall survival in patients with metastatic PD-L1 positive triple negative breast cancer (TNBC). Atezolizumab with anthracycline- and taxane-based neoadjuvant chemotherapy has also shown increased pathological complete response (pCR) rates in early TNBC. This trial evaluated neoadjuvant carboplatin and paclitaxel with or without atezolizumab in patients with clinical stages II-III TNBC. The co-primary objectives were to evaluate if chemotherapy and atezolizumab increase pCR rate and tumor infiltrating lymphocyte (TIL) percentage compared to chemotherapy alone in the mITT population. Sixty-seven patients (ages 25-78 years; median, 52 years) were randomly assigned - 22 patients to Arm A, and 45 to Arm B. Median follow up was 6.6 months. In the modified intent to treat population (all patients evaluable for the primary endpoints who received at least one dose of combination therapy), the pCR rate was 18.8% (95% CI 4.0-45.6%) in Arm A, and 55.6% (95% CI 40.0-70.4%) in Arm B (estimated treatment difference: 36.8%, 95% CI 8.5-56.6%; p = 0.018). Grade 3 or higher treatment-related adverse events occurred in 62.5% of patients in Arm A, and 57.8% of patients in Arm B. One patient in Arm B died from recurrent disease during the follow-up period. TIL percentage increased slightly from baseline to cycle 1 in both Arm A (mean ± SD: 0.6% ± 21.0%) and Arm B (5.7% ± 15.8%) (p = 0.36). Patients with pCR had higher median TIL percentages (24.8%) than those with non-pCR (14.2%) (p = 0.02). Although subgroup analyses were limited by the small sample size, PD-L1-positive patients treated with chemotherapy and atezolizumab had a pCR rate of 75% (12/16). The addition of atezolizumab to neoadjuvant carboplatin and paclitaxel resulted in a statistically significant and clinically relevant increased pCR rate in patients with clinical stages II and III TNBC. (Funded by National Cancer Institute)

Evaluation of copanlisib in combination with eribulin in triple-negative breast cancer patient-derived xenograft models

UNLABELLED: The PI3K pathway regulates essential cellular functions and promotes chemotherapy resistance. Activation of PI3K pathway signaling is commonly observed in triple-negative breast cancer (TNBC). However previous studies that combined PI3K pathway inhibitors with taxane regimens have yielded inconsistent results. We therefore set out to examine whether the combination of copanlisib, a clinical grade pan-PI3K inhibitor, and eribulin, an antimitotic chemotherapy approved for taxane-resistant metastatic breast cancer, improves the antitumor effect in TNBC. A panel of eight TNBC patient-derived xenograft (PDX) models was tested for tumor growth response to copanlisib and eribulin, alone or in combination. Treatment-induced signaling changes were examined by reverse phase protein array, immunohistochemistry (IHC) and 18F-fluorodeoxyglucose PET (18F-FDG PET). Compared with each drug alone, the combination of eribulin and copanlisib led to enhanced tumor growth inhibition, which was observed in both eribulin-sensitive and -resistant TNBC PDX models, regardless of PI3K pathway alterations or PTEN status. Copanlisib reduced PI3K signaling and enhanced eribulin-induced mitotic arrest. The combination enhanced induction of apoptosis compared with each drug alone. Interestingly, eribulin upregulated PI3K pathway signaling in PDX tumors, as demonstrated by increased tracer uptake by 18F-FDG PET scan and AKT phosphorylation by IHC. These changes were inhibited by the addition of copanlisib. These data support further clinical development for the combination of copanlisib and eribulin and led to a phase I/II trial of copanlisib and eribulin in patients with metastatic TNBC. SIGNIFICANCE: In this research, we demonstrated that the pan-PI3K inhibitor copanlisib enhanced the cytotoxicity of eribulin in a panel of TNBC PDX models. The improved tumor growth inhibition was irrespective of PI3K pathway alteration and was corroborated by the enhanced mitotic arrest and apoptotic induction observed in PDX tumors after combination therapy compared with each drug alone. These data provide the preclinical rationale for the clinical testing in TNBC

Proteomic resistance biomarkers for PI3K inhibitor in triple negative breast cancer patient-derived xenograft models

PI3K pathway activation is frequently observed in triple negative breast cancer (TNBC). However, single agent PI3K inhibitors have shown limited anti-tumor activity. To investigate biomarkers of response and resistance mechanisms, we tested 17 TNBC patient-derived xenograft (PDX) models representing diverse genomic backgrounds and varying degrees of PI3K pathway signaling activities for their tumor growth response to the pan-PI3K inhibitor, BKM120. Baseline and post-treatment PDX tumors were subjected to reverse phase protein array (RPPA) to identify protein markers associated with tumor growth response. While BKM120 consistently reduced PI3K pathway activity, as demonstrated by reduced levels of phosphorylated AKT, percentage tumor growth inhibition (%TGI) ranged from 35% in the least sensitive to 84% in the most sensitive model. Several biomarkers showed significant association with resistance, including elevated baseline levels of growth factor receptors (EGFR, pHER3 Y1197), PI3Kp85 regulatory subunit, anti-apoptotic protein BclXL, EMT (Vimentin, MMP9, IntegrinaV), NFKB pathway (IkappaB, RANKL), and intracellular signaling molecules including Caveolin, CBP, and KLF4, as well as treatment-induced increases in the levels of phosphorylated forms of Aurora kinases. Interestingly, increased AKT phosphorylation or PTEN loss at baseline were not significantly correlated to %TGI. These results provide important insights into biomarker development for PI3K inhibitors in TNBC