The backbone of ovarian cancer treatment is platinum-based chemotherapy and aggressive surgical debulking. New therapeutic approaches using immunotherapy via immune checkpoint blockade, which have demonstrated clinical efficacy in other tumor types, have been less promising in ovarian cancer. To increase their clinical efficacy, checkpoint inhibitors are now being tested in clinical trials in combination with chemotherapy. Here, we evaluated the impact of cisplatin on tumor immunogenicity and its in vivo roles when used alone or in combination with anti-PD-L1, in two novel murine ovarian cancer cell models. The 2F8 and its platinum-resistant derivative 2F8cis model, display distinct inflammatory profiles and chemotherapy sensitivities, and mirror the primary and recurrent human disease, respectively. Acute and chronic exposure to cisplatin enhances tumor immunogenicity by increasing calreticulin, MHC class I, antigen presentation and T cell infiltration. Cisplatin also upregulates PD-L1 expression in vitro and in vivo, demonstrating a dual, paradoxical immune modulatory effect and supporting the rationale for combination with immune checkpoint blockade. One of the pathways activated by cisplatin treatment is the cGAS/STING pathway. Chronic cisplatin treatment led to upregulation of cGAS and STING proteins in 2F8cis compared to parental 2F8 cells, while acute exposure to cisplatin further increases cGAS and STING levels in both 2F8 and 2F8cis cells. Overexpression of cGAS/STING modifies tumor immunogenicity by upregulating PD-L1, MHC I and calreticulin in tumor cells. Anti-PD-L1 alone in a platinum-sensitive model or with cisplatin in a platinum-resistant model increases survival. These studies have high translational potential in ovarian cancer.

Estrogen receptor alpha (ER/ESR1) is frequently mutated in endocrine resistant ER-positive (ER+) breast cancer and linked to ligand-independent growth and metastasis. Despite the distinct clinical features of ESR1 mutations, their role in intrinsic subtype switching remains largely unknown. Here we find that ESR1 mutant cells and clinical samples show a significant enrichment of basal subtype markers, and six basal cytokeratins (BCKs) are the most enriched genes. Induction of BCKs is independent of ER binding and instead associated with chromatin reprogramming centered around a progesterone receptor-orchestrated insulated neighborhood. BCK-high ER+ primary breast tumors exhibit a number of enriched immune pathways, shared with ESR1 mutant tumors. S100A8 and S100A9 are among the most induced immune mediators and involve in tumor-stroma paracrine crosstalk inferred by single-cell RNA-seq from metastatic tumors. Collectively, these observations demonstrate that ESR1 mutant tumors gain basal features associated with increased immune activation, encouraging additional studies of immune therapeutic vulnerabilities.

The progress in the field of high-dimensional cytometry has greatly increased the number of markers that can be simultaneously analyzed producing datasets with large numbers of parameters. Traditional biaxial manual gating might not be optimal for such datasets. To overcome this, a large number of automated tools have been developed to aid with cellular clustering of multi-dimensional datasets. Here were review two large categories of such tools; unsupervised and supervised clustering tools. After a thorough review of the popularity and use of each of the available unsupervised clustering tools, we focus on the top six tools to discuss their advantages and limitations. Furthermore, we employ a publicly available dataset to directly compare the usability, speed, and relative effectiveness of the available unsupervised and supervised tools. Finally, we discuss the current challenges for existing methods and future direction for the new generation of cell type identification approaches.

IMPORTANCE Overtreatment of early-stage breast cancer with favorable tumor biology in older patients may be harmful without affecting recurrence and survival. Guidelines that recommend deimplementation of sentinel lymph node biopsy (SLNB) (Choosing Wisely) and radiotherapy (RT) (National Comprehensive Cancer Network) have been published. OBJECTIVE To describe the use rates and association with disease recurrence of SLNB and RT in older women with breast cancer. DESIGN, SETTING, AND PARTICIPANTS This cohort study obtained patient and clinical data from an integrated cancer registry and electronic health record of a single health care system in Pennsylvania. The cohort was composed of consecutive female patients 70 years or older who were diagnosed with early-stage, estrogen receptor-positive, ERBB2 (formerly HER2)-negative, clinically node-negative breast cancer from January 1, 2010, to December 31, 2018, who were treated at 15 community and academic hospitals within the health system. EXPOSURES Sentinel lymph node biopsy and adjuvant RT. MAIN OUTCOMES AND MEASURES Primary outcomes were 5-year locoregional recurrence-free survival (LRFS) rate and disease-free survival (DFS) rate after SLNB and after RT. Secondary outcomes included recurrence rate, subgroups that may benefit from SLNB or RT, and use rate of SLNB and RT over time. Propensity scores were used to create 2 cohorts to separately evaluate the association of SLNB and RT with recurrence outcomes. Cox proportional hazards regression model was used to estimate hazard ratios (HRs). RESULTS From 2010 to 2018, a total of 3361 women 70 years or older (median [interquartile range {IQR}] age, 77.0 [73.0-82.0] years) with estrogen receptor-positive, ERBB2-negative, clinically nodenegative breast cancer were included in the study. Of these women, 2195 (65.3%) received SLNB and 1828 (54.4%) received adjuvant RT. Rates of SLNB steadily increased (1.0% per year), a trend that persisted after the 2016 adoption of the Choosing Wisely guideline. Rates of RT decreased slightly (3.4% per year). To examine patient outcomes and maximize follow-up time, the analysis was limited to cases from 2010 to 2014, identifying 2109 patients with a median (IQR) follow-up time of 4.1 (2.5-5.7) years. In the propensity score-matched cohorts, no association was found between

Psychiatric disorders are associated with accelerated aging and enhanced risk for neurodegenerative disorders. Brain aging is associated with molecular, cellular and structural changes that are robust on the group-level, yet show substantial inter-individual variability. Here we assessed deviations in gene expression from normal age-dependent trajectories, and tested their validity as predictors of risk for major mental illnesses and neurodegenerative disorders. We performed large-scale gene expression and genotype analyses in postmortem samples of two frontal cortical brain regions from 214 control subjects aged 20–90 years. Individual estimates of “molecular age” were derived from age-dependent genes, identified by robust regression analysis. Deviation from chronological age was defined as “delta age”. Genetic variants associated with deviations from normal gene expression patterns were identified by expression quantitative trait loci (cis-eQTL) of age-dependent genes or genome-wide association study (GWAS) on delta age, combined into distinct polygenic risk scores (PRS cis-eQTL and PRS GWAS ), and tested for predicting brain disorders or pathology in independent postmortem expression datasets and clinical cohorts. In these validation datasets, molecular ages, defined by 68 and 76 age-related genes for two brain regions respectively, were positively correlated with chronological ages (r=0.88/0.91), elevated in bipolar disorder (BP) and schizophrenia (SCZ), and unchanged in major depressive disorder (MDD). Exploratory analyses in independent clinical datasets show that PRSs were associated with SCZ and MDD diagnostics, and with cognition in SCZ and pathology in Alzheimer’s disease (AD). These results suggest that older molecular brain aging is a common feature of severe mental illnesses and neurodegeneration.