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Microglia play a role in the emergence and preservation of a healthy brain microenvironment. Dysfunction of microglia has been associated with neurodevelopmental and neurodegenerative disorders. Investigating the function of human microglia in health and disease has been challenging due to the limited models of the human brain available. Here, we develop a method to generate functional microglia in human cortical organoids (hCOs) from human embryonic stem cells (hESCs). We apply this system to study the role of microglia during inflammation induced by amyloid-β (Aβ). The overexpression of the myeloid-specific transcription factor PU.1 generates microglia-like cells in hCOs, producing mhCOs (microglia-containing hCOs), that we engraft in the mouse brain. Single-cell transcriptomics reveals that mhCOs acquire a microglia cell cluster with an intact complement and chemokine system. Functionally, microglia in mhCOs protect parenchyma from cellular and molecular damage caused by Aβ. Furthermore, in mhCOs, we observed reduced expression of Aβ-induced expression of genes associated with apoptosis, ferroptosis, and Alzheimer’s disease (AD) stage III. Finally, we assess the function of AD-associated genes highly expressed in microglia in response to Aβ using pooled CRISPRi coupled with single-cell RNA sequencing in mhCOs. In summary, we provide a protocol to generate mhCOs that can be used in fundamental and translational studies as a model to investigate the role of microglia in neurodevelopmental and neurodegenerative disorders. The study of human microglia function in health and disease is limited by the availability of sound models. Here, the authors develop a method to generate functional microglia in human cortical organoids and investigate the role of human microglia during amyloid beta1-42- induced inflammation.

Ki67, a nuclear proliferation-related protein, is heavily used in anatomic pathology but has not become a companion diagnostic or a standard-of-care biomarker due to analytic variability in both assay protocols and interpretation. The International Ki67 Working Group in breast cancer has published and has ongoing efforts in the standardization of the interpretation of Ki67, but they have not yet assessed technical issues of assay production representing multiple sources of variation, including antibody clones, antibody formats, staining platforms, and operators. The goal of this work is to address these issues with a new standardization tool. We have developed a cell line microarray system in which mixes of human Karpas 299 or Jurkat cells (Ki67+) with Sf9 (Spodoptera frugiperda) (Ki67-) cells are present in incremental standardized ratios. To validate the tool, six different antibodies, including both ready-to-use and concentrate formats from six vendors, were used to measure Ki67 proliferation indices using IHC protocols for manual (bench-top) and automated platforms. The assays were performed by three different laboratories at Yale and analyzed using two image analysis software packages, including QuPath and Visiopharm. Results showed statistically significant differences in Ki67 reactivity between each antibody clone. However, subsets of Ki67 assays using three clones performed in three different labs show no significant differences. This work shows the need for analytic standardization of the Ki67 assay and provides a new tool to do so. We show here how a cell line standardization system can be used to normalize the staining variability in proliferation indices between different antibody clones in a triple negative breast cancer cohort. We believe that this cell line standardization array has the potential to improve reproducibility among Ki67 assays and laboratories, which is critical for establishing Ki67 as a standard-of-care assay.

Many aspects of the evolutionary process of tumorigenesis that are fundamental to cancer biology and targeted treatment have been challenging to reveal, such as the divergence times and genetic clonality of metastatic lineages. To address these challenges, we performed tumor phylogenetics using molecular evolutionary models, reconstructed ancestral states of somatic mutations, and inferred cancer chronograms to yield three conclusions. First, in contrast to a linear model of cancer progression, metastases can originate from divergent lineages within primary tumors. Evolved genetic changes in cancer lineages likely affect only the proclivity toward metastasis. Single genetic changes are unlikely to be necessary or sufficient for metastasis. Second, metastatic lineages can arise early in tumor development, sometimes long before diagnosis. The early genetic divergence of some metastatic lineages directs attention toward research on driver genes that are mutated early in cancer evolution. Last, the temporal order of occurrence of driver mutations can be inferred from phylogenetic analysis of cancer chronograms, guiding development of targeted therapeutics effective against primary tumors and metastases.

The goal of this Phase I/II trial is to assess the safety and efficacy of administering durvalumab concurrent with weekly nab-paclitaxel and dose-dense doxorubicin/cyclophosphamide (ddAC) neoadjuvant therapy for stages I–III triple-negative breast cancer. The primary endpoint is pathologic complete response (pCR:ypT0/is, ypN0). The response was correlated with PDL1 expression and stromal tumor-infiltrating lymphocytes (sTILs). Two dose levels of durvalumab (3 and 10 mg/kg) were assessed. PD-L1 was assessed using the SP263 antibody; ≥1% immune and tumor cell staining was considered positive; sTILs were calculated as the area occupied by mononuclear inflammatory cells over the total intratumoral stromal area. 59 patients were evaluable for toxicity and 55 for efficacy in the Phase II study (10 mg/kg dose). No dose-limiting toxicities were observed in Phase I. In Phase II, pCR rate was 44% (95% CI: 30–57%); 18 patients (31%) experienced grade 3/4 treatment-related adverse events (AE), most frequently neutropenia ( n  = 4) and anemia ( n  = 4). Immune-related grade 3/4 AEs included Guillain–Barre syndrome ( n  = 1), colitis ( n  = 2), and hyperglycemia ( n  = 2). Of the 50 evaluable patients for PD-L1, 31 (62%) were PD-L1 positive. pCR rates were 55% (95% CI: 0.38–0.71) and 32% (95% CI: 0.12–0.56) in the PD-L1 positive and negative groups ( p  = 0.15), respectively. sTIL counts were available on 52 patients and were significantly higher in the pCR group ( p  = 0.0167). Concomitant administration of durvalumab with sequential weekly nab-paclitaxel and ddAC neoadjuvant chemotherapy resulted in a pCR rate of 44%; pCR rates were higher in sTIL-high cancers.

Background: Clinical options for patients harbouring advanced/recurrent uterine serous carcinoma (USC), an aggressive variant of endometrial tumour, are very limited. Next-generation sequencing (NGS) data recently demonstrated that cyclin E1 (CCNE1) gene amplification and pik3ca driver mutations are common in USC and may therefore represent ideal therapeutic targets. Methods: Cyclin E1 expression was evaluated by immunohistochemistry (IHC) on 95 USCs. The efficacy of the cyclin-dependent kinase 2/9 inhibitor CYC065 was assessed on multiple primary USC cell lines with or without CCNE1 amplification. Cell-cycle analyses and knockdown experiments were performed to assess CYC065 targeting specificity. Finally, the in vitro and in vivo activity of CYC065, Taselisib (a PIK3CA inhibitor) and their combinations was tested on USC xenografts derived from CCNE1-amplified/ pik3ca -mutated USCs. Results: We found that 89.5% of the USCs expressed CCNE1. CYC065 blocked cells in the G1 phase of the cell cycle and inhibited cell growth specifically in CCNE1-overexpressing USCs. Cyclin E1 knockdown conferred increased resistance to CYC065, whereas CYC065 treatment of xenografts derived from CCNE1-amplified USCs significantly reduced tumour growth. The combination of CYC065 and Taselisib demonstrated synergistic effect in vitro and was significantly more effective than single-agent treatment in decreasing tumour growth in xenografts of CCNE1-amplified/ pik3ca -mutated USCs. Conclusions: Dual CCNE1/PIK3CA blockade may represent a novel therapeutic option for USC patients harbouring recurrent CCNE1-amplified/ pi3kca -mutated tumours.

Pre-analytic variables, specifically cold ischemic time, have been implicated as key variables in the measurement of proteins by immunohistochemistry. To determine the significance and magnitude of antigenic loss due to pre-analytic variables, we have compared protein antigenicity in core needle biopsies, with essentially no cold ischemic time, with that in routinely processed tumor resection specimens. Two cohorts of matched core needle biopsies and tumor resections were collected with 20 matched pairs and 14 matched pairs, respectively. Both series were analyzed by quantitative immunofluorescence using the AQUA® method. Epitopes phospho-ERK, total ERK, phospho-AKT, total AKT, phospho-S6K1, total S6K1, estrogen receptor (ER), Ki67, cytokeratin and GAPDH were assessed. Detection levels for all phospho-epitopes were significantly decreased in tumor resections compared with biopsies while no significant change was seen in the corresponding total proteins. Of the other four proteins examined, ER and cytokeratin showed significant loss of antigenicity. This data suggest that measurement of phospho-protein antigenicity in formalin-fixed tissue by immunological methods is dramatically affected by pre-analytic variables. This study suggests that core needle biopsies are more accurate for assessment of tissue biomarkers.

Emerging data indicate that genomic alterations can shape immune cell composition in early breast cancer. However, there is a need for complementary imaging and sequencing methods for the quantitative assessment of combined somatic copy number alteration (SCNA) and immune profiling in pathological samples. Here, we tested the feasibility of three approaches—CUTseq, for high-throughput low-input SCNA profiling, multiplexed fluorescent immunohistochemistry (mfIHC) and digital-image analysis (DIA) for quantitative immuno-profiling- in archival formalin-fixed paraffin-embedded (FFPE) tissue samples from patients enrolled in the randomized SBG-2004-1 phase II trial. CUTseq was able to reproducibly identify amplification and deletion events with a resolution of 100 kb using only 6 ng of DNA extracted from FFPE tissue and pooling together 77 samples into the same sequencing library. In the same samples, mfIHC revealed that CD4 + T-cells and CD68 + macrophages were the most abundant immune cells and they mostly expressed PD-L1 and PD-1. Combined analysis showed that the SCNA burden was inversely associated with lymphocytic infiltration. Our results set the basis for further applications of CUTseq, mfIHC and DIA to larger cohorts of early breast cancer patients.

Differences in the tumor immune microenvironment may result in differences in prognosis and response to treatment in cancer patients. We hypothesized that differences in the tumor immune microenvironment may exist between African American (AA) and NonAA patients, due to ancestry-related or socioeconomic factors, that may partially explain differences in clinical outcomes. We analyzed clinically matched triple-negative breast cancer (TNBC) tissues from self-identified AA and NonAA patients and found that stromal TILs, PD-L1 IHC-positivity, mRNA expression of immune-related pathways, and immunotherapy response predictive signatures were significantly higher in AA samples (p < 0.05; Fisher’s Exact Test, Mann–Whitney Test, Permutation Test). Cancer biology and metabolism pathways, TAM-M2, and Immune Exclusion were significantly higher in NonAA samples (p < 0.05; Permutation Test, Mann–Whitney Test). There were no differences in somatic tumor mutation burden. Overall, there is greater immune infiltration and inflammation in AA TNBC and these differences may impact response to immune checkpoint inhibitors and other therapeutic agents that modulate the immune microenvironment.

Breast cancer (BC) represents a heterogeneous ecosystem and elucidation of tumor microenvironment components remains essential. Our study aimed to depict the composition and prognostic correlates of immune infiltrate in early BC, at a multiplex and spatial resolution. Pretreatment tumor biopsies from patients enrolled in the EORTC 10994/BIG 1-00 randomized phase III neoadjuvant trial (NCT00017095) were used; the CNN11 classifier for H&E-based digital TILs (dTILs) quantification and multiplex immunofluorescence were applied, coupled with machine learning (ML)-based spatial features. dTILs were higher in the triple-negative (TN) subtype, and associated with pathological complete response (pCR) in the whole cohort. Total CD4+ and intra-tumoral CD8+ T-cells expression was associated with pCR. Higher immune-tumor cell colocalization was observed in TN tumors of patients achieving pCR. Immune cell subsets were enriched in TP53 -mutated tumors. Our results indicate the feasibility of ML-based algorithms for immune infiltrate characterization and the prognostic implications of its abundance and tumor-host interactions.

We assessed the predictive value of an image analysis-based tumor-infiltrating lymphocytes (TILs) score for pathologic complete response (pCR) and event-free survival in breast cancer (BC). About 113 pretreatment samples were analyzed from patients with stage IIB-IIIC HER-2-negative BC randomized to neoadjuvant chemotherapy ± bevacizumab. TILs quantification was performed on full sections using QuPath open-source software with a convolutional neural network cell classifier (CNN11). We used easTILs% as a digital metric of TILs score defined as [sum of lymphocytes area (mm2)/stromal area(mm2)] × 100. Pathologist-read stromal TILs score (sTILs%) was determined following published guidelines. Mean pretreatment easTILs% was significantly higher in cases with pCR compared to residual disease (median 36.1 vs.14.8%, p < 0.001). We observed a strong positive correlation (r = 0.606, p < 0.0001) between easTILs% and sTILs%. The area under the prediction curve (AUC) was higher for easTILs% than sTILs%, 0.709 and 0.627, respectively. Image analysis-based TILs quantification is predictive of pCR in BC and had better response discrimination than pathologist-read sTILs%.