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Purpose: Cyclin-dependent kinase (CDK) 4/6 drives cell proliferation in estrogen receptor–positive (ER+) breast cancer. This single-arm phase II neoadjuvant trial (NeoPalAna) assessed the antiproliferative activity of the CDK4/6 inhibitor palbociclib in primary breast cancer as a prelude to adjuvant studies.Experimental Design: Eligible patients with clinical stage II/III ER+/HER2− breast cancer received anastrozole 1 mg daily for 4 weeks (cycle 0; with goserelin if premenopausal), followed by adding palbociclib (125 mg daily on days 1–21) on cycle 1 day 1 (C1D1) for four 28-day cycles unless C1D15 Ki67 > 10%, in which case patients went off study due to inadequate response. Anastrozole was continued until surgery, which occurred 3 to 5 weeks after palbociclib exposure. Later patients received additional 10 to 12 days of palbociclib (Cycle 5) immediately before surgery. Serial biopsies at baseline, C1D1, C1D15, and surgery were analyzed for Ki67, gene expression, and mutation profiles. The primary endpoint was complete cell cycle arrest (CCCA: central Ki67 ≤ 2.7%).Results: Fifty patients enrolled. The CCCA rate was significantly higher after adding palbociclib to anastrozole (C1D15 87% vs. C1D1 26%, P < 0.001). Palbociclib enhanced cell-cycle control over anastrozole monotherapy regardless of luminal subtype (A vs. B) and PIK3CA status with activity observed across a broad range of clinicopathologic and mutation profiles. Ki67 recovery at surgery following palbociclib washout was suppressed by cycle 5 palbociclib. Resistance was associated with nonluminal subtypes and persistent E2F-target gene expression.Conclusions: Palbociclib is an active antiproliferative agent for early-stage breast cancer resistant to anastrozole; however, prolonged administration may be necessary to maintain its effect. Clin Cancer Res; 23(15); 4055–65. ©2017 AACR.

Supplementary Table S1 describes the AE profile, Supplementary S2 shows the results of clinical and radiologic responses.

Supplementary Table S3 provides the result of the 83-gene panel next generation sequencing

Supplementary Fig. S1 is the consort diagram; Supplementary Fig. S2 describes the clinicopathologic and molecular features of the 6 palbociclib resistant tumors; Supplementary Fig S3 shows the proliferation score and correlation with Ki67 at each time point; Supplementary Fig S4 shows the heatmap of the proliferation score genes and ER regulated genes

The caption provides the title and description for the Supplementary Tables S3 adn S4.

Purpose: Patients with triple negative breast cancer (TNBC) who do not achieve pathological complete response (pCR) following neoadjuvant chemotherapy have a high risk of recurrence and death. Molecular characterization may identify patients unlikely to achieve pCR. This neoadjuvant trial was conducted to determine the pCR rate with docetaxel and carboplatin, and to identify molecular alterations and/or immune gene signatures predicting pCR.Experimental Design: Patients with clinical stages II/III TNBC received 6 cycles of docetaxel and carboplatin. The primary objective was to determine if neoadjuvant docetaxel and carboplatin would increase the pCR rate in TNBC compared to historical expectations. We performed whole exome sequencing (WES) and immune profiling on pre-treatment tumor samples to identify alterations that may predict pCR. Thirteen matching on-treatment samples were also analyzed to assess changes in molecular profiles.Results: Fifty-eight of 127 (45.7%) patients achieved pCR. There was a non-significant trend towards higher mutation burden for patients with residual cancer burden (RCB) 0/I versus RCB II/III (median 80, versus 68 variants, p 0.88). TP53 was the most frequently mutated gene, observed in 85.7% of tumors. EGFR, RB1, RAD51AP2, SDK2, L1CAM, KPRP, PCDHA1, CACNA1S, CFAP58, COL22A1, and COL4A5 mutations were observed almost exclusively in pre-treatment samples from patients who achieved pCR. Seven mutations in PCDHA1 were observed in pre-treatment samples from patients who did not achieve pCR. Several immune gene signatures including IDO1, PD-L1, interferon gamma signaling, CTLA4, cytotoxicity, tumor inflammation signature, inflammatory chemokines, cytotoxic cells, lymphoid, PD-L2, exhausted CD8, Tregs, and immunoproteosome were upregulated in pre-treatment samples from patients who achieved pCR.Conclusions: Neoadjuvant docetaxel and carboplatin resulted in a pCR of 45.7%. WES and immune profiling differentiated patients with and without pCR. Trial registration: Clinical trial information: NCT02124902, Registered 24 April 2014, & NCT02547987, Registered 10 September 2015.

Spatial transcriptomics (ST) and CO-Detection by indEXing (CODEX) are becoming the leading transformative approaches for studying spatially resolved tumor heterogeneity and immune complexity. To explore the application of these two cutting-edge technologies and to further investigate the complexities of tumor microenvironment, we applied 10x Visium Gene Expression platform and Akoya CODEX platform on surgical resections from pancreatic ductal adenocarcinoma (PDAC), breast cancer (BRCA), and clear cell renal carcinoma (ccRCC) patients. A total of 30+ protein markers were screened, verified, and conjugated as CODEX antibodies for the 3 types of cancers. Tumor microenvironment was vividly revealed by a set of cancer markers, immune markers, and stroma cells markers on a single ST slide and a single CODEX image. Notably, the distinct immune microenvironment was observed between tumor nests in the neighborhood in terms of cell types, number of cells, and cell distribution patterns. This work highlights the importance of direct visualization for tumor heterogeneity. It also provides a significant insight for understanding tumor complexity and a promising opportunity to benefit personalized medicine. Citation Format: Siqi Chen, Andrew Shinkle, Yanyan Zhao, Chia-Kuei Mo, Andrew Houston, Preet Lal, John M. Herndon, Ryan C. Fields, William Gillanders, Feng Chen, Li Ding. Spatial transcriptomics and multiplexed imaging to explore tumor heterogeneity and immune complexity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1710.

Neoantigens are novel peptide sequences resulting from somatic mutations in tumors that upon loading onto major histocompatibility complex (MHC) molecules allow recognition by T cells. Accurate neoantigen identification is thus critical for designing cancer vaccines and predicting response to immunotherapies. Neoantigen identification and prioritization relies on correctly inferring whether the presenting peptide sequence can successfully induce an immune response. As the majority of somatic mutations are SNVs, changes between wildtype and mutant peptide are subtle and require cautious interpretation. An important, yet underappreciated, variable in neoantigen-prediction pipelines is the mutation position within the peptide relative to its anchor positions for the patient’s specific HLA alleles. While a subset of peptide positions are presented to the T-cell receptor for recognition, others are responsible for anchoring to the MHC, making these positional considerations critical for predicting T-cell responses. However, a systematic method for determining anchor locations for the wide range of HLA alleles present in the population and application of these to evaluate MT/WT peptide pairs arising in tumors has not been reported. As a result, many neoantigen studies have either failed to adequately consider this crucial factor or have used conventional assumptions to guide their neoantigen identification process. Here, we provide a computational workflow for predicting anchor locations for a wide range of HLA alleles, using a reference dataset generated from clinical and The Cancer Genome Atlas (TCGA) patient samples. We calculated high probability anchor positions for different peptide lengths for over 300 common HLA alleles. Analysis of these results showed clusters of different anchor trends among the HLA alleles analyzed. A subset of these HLA anchor results were orthogonally validated using protein crystallography structures. Analysis of 923 tumor samples showed that 7-41% of neoantigen candidates were potentially misclassified in the neoantigen selection process and can be rescued using allele-specific knowledge of anchor positions. These anchor predictions are currently undergoing experimental validation using both peptide-MHC stability assays as well as fluorescence-based competition binding assays. By incorporating our anchor prediction results into neoantigen prediction pipelines, such as pVACtools, we hope to formalize and streamline the identification process for relevant clinical studies. Citation Format: Huiming Xia, Joshua McMichael, Michelle Becker-Hapak, Onyinyechi C. Onyeador, Rico Buchli, Ethan McClain, Patrick Pence, Suangson Supabphol, Megan M. Richters, Anamika Basu, Cody A. Ramirez, Cristina Puig-Saus, Kelsy C. Cotto, Jasreet Hundal, Susanna Kiwala, S. Peter Goedegebuure, Tanner M. Johanns, Gavin P. Dunn, Antoni Ribas, Christopher A. Miller, William Gillanders, Todd A. Fehniger, Obi L. Griffith, Malachi Griffith. Computational prediction of MHC anchor locations guide neoantigen prediction and prioritization [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5639.

This protocol describes the preparation and staining of human FFPE material for multiplex visualization using Imaging Mass Cytometry (IMC). This protocol uses basic standard immunohistochemical staining techniques. The tissue is incubated with antibodies that have specific affinity for different cells and tissues in the context of a formalin fixed thin section of human tumor material. Antibodies are labeled with heavy metals instead of the typical fluorochromes, and are visualized using the Hyperion Imaging System manufactured by the Fluidigm corporation.

Purpose To determine the impact of a physiciandirected, multifaceted health information technology (HIT) system on diabetes outcomes. Methods A pre/post-interventional study. Setting and participants The setting was Providence Primary Care Research Network in Oregon, with approximately 71 physicians caring for 117 369 patients in 13 clinic locations. The study covered Network patients with diabetes age 18 years and older. Intervention The study intervention included implementation of the CareManagerTM HIT system which augments an electronic medical record (EMR) by automating physician driven quality improvement interventions, including point-of-care decision support and care reminders, diabetes registry with care prompts, performance feedback with benchmarking and access to published evidence and patient educational materials. Measures The primary clinical measures included the change in mean value for low density lipoprotein (LDL) target Results A total of 6072 patients were identified at baseline, 70% of whom were continuously enrolled during the 24-month study. Significant improvements were observed in all diabetes related outcomes except mean HbA1c. LDL goal attainment improved from 32% to 56% (P=0.002), while mean LDL decreased by 13 mg/dL (0.33 mmol/l, P=0.002). BP goal attainment increased significantly from 30% to 52%, with significant decreases in both mean systolic and diastolic BP. The proportion of patients with an HbA1c below 7% was higher at the end of the study (P=0.008). Mean patient satisfaction remained high, with no significant difference between baseline and follow-up. Total Relative Value Units per patient per year significantly increased as a result of an increase in the number of visits in year one and the coding complexity throughout. Conclusion Implementation of a physician-directed, multifaceted HIT system in primary care was associated with significantly improved diabetes process and outcome measures.

Creative, cost-effective interventions to improve the quality of care of chronic illnesses are needed. This study was designed to evaluate the impact of remote physician-pharmacist team-based care on cholesterol levels in patients with diabetes mellitus (DM).This 2-year prospective, cluster randomized controlled trial was conducted within the Providence Primary Care Research Network in Oregon. Participants at least 18 years of age were identified by a diagnosis of DM. The intervention included remote physician-pharmacist team-based care focused on cholesterol management in DM. All clinicians in the study had access to the health information technology tool CareManager, which provided automated DM-related point-of-care prompts, a Web-based registry, and performance feedback with benchmarking. Study outcomes included the difference in low-density lipoprotein cholesterol (LDL-C) goal attainment, mean LDL-C, prescribed lipid-lowering therapy, and patient satisfaction between the intervention and control arms.A total of 6963 patients with DM cared for by 68 physicians in 9 clinics were evaluated. Patients in the intervention arm were more likely to achieve their target LDL-C levels compared with controls (78% vs 50%; P = .003). The mean LDL-C level was 12 mg/dL lower in the intervention arm compared with the control arm (P.001). The rate of LDL-C testing was significantly higher in the intervention arm compared with the control arm. Patients in the intervention arm were also 15% more likely to receive a prescription for a lipid-lowering medication (P = .008). There was no significant difference in patient satisfaction between study arms (P = .15).Remotely located physician-pharmacist team-based care resulted in significantly improved LDL-C levels and goal attainment among patients with DM.

Mammaglobin-A (Mam-A), a 10kD secretory protein, is over expressed in 80% of primary and metastatic human breast cancers. Previous studies in our laboratory using a HLA-A2/Human CD8 transgenic murine model have demonstrated that Mam-A DNA Vaccine elicit specific CD8+ cytotoxic T-cell (CTL) responses to Mam-A and induces tumour regression in SCID mice. In our current study we report the activation of T-helper cells with specific expression of ICOS (inducible costimulator), a T-cell specific activation marker, following Mam-A vaccination. Stage IV breast cancer patients were chosen for the study and vaccinated by Mam-A DNA vaccine on 0, 28 and 56 days. Six months following Mam-A vaccination (n=5), flow cytometry analysis demonstrated a increase in CD4+ICOS+ T-cell frequency from 5±2% to 23± 4% with a concomitant drop in the CD4+Foxp3+T-cell (Treg) frequency from 19±6% to 10±5%. However, the frequency of CD4+CD25+ICOS+ did not change following vaccination (23±5%). ELISpot analysis demonstrated that following vaccination, CD4+ICOS+ sorted T-cells demonstrated a cytokine phenotype switch from IL-10 to IFN-γ. We conclude that following Mam-A DNA vaccination, there is a specific activation T-cells with increase in the pro-inflammatory IFN-γ CD4+ICOS+T-cells along with decrease in Treg frequency. We propose that this switch in T-cell frequency following vaccination may be important in tumor regression in breast cancer patients.