Predictability of B cell clonal persistence and immunosurveillance in breast cancer.

B cells and T cells are important components of the adaptive immune system and mediate anticancer immunity. The T cell landscape in cancer is well characterized, but the contribution of B cells to anticancer immunosurveillance is less well explored. Here we show an integrative analysis of the B cell and T cell receptor repertoire from individuals with metastatic breast cancer and individuals with early breast cancer during neoadjuvant therapy. Using immune receptor, RNA and whole-exome sequencing, we show that both B cell and T cell responses seem to coevolve with the metastatic cancer genomes and mirror tumor mutational and neoantigen architecture. B cell clones associated with metastatic immunosurveillance and temporal persistence were more expanded and distinct from site-specific clones. B cell clonal immunosurveillance and temporal persistence are predictable from the clonal structure, with higher-centrality B cell antigen receptors more likely to be detected across multiple metastases or across time. This predictability was generalizable across other immune-mediated disorders. This work lays a foundation for prioritizing antibody sequences for therapeutic targeting in cancer.

Prediction of cancer treatment response from histopathology images through imputed transcriptomics.

Advances in artificial intelligence have paved the way for leveraging hematoxylin and eosin (H&E)-stained tumor slides for precision oncology. We present ENLIGHT-DeepPT, an approach for predicting response to multiple targeted and immunotherapies from H&E-slides. In difference from existing approaches that aim to predict treatment response directly from the slides, ENLIGHT-DeepPT is an indirect two-step approach consisting of (1) DeepPT, a new deep-learning framework that predicts genome-wide tumor mRNA expression from slides, and (2) ENLIGHT, which predicts response based on the DeepPT inferred expression values. DeepPT successfully predicts transcriptomics in all 16 TCGA cohorts tested and generalizes well to two independent datasets. Our key contribution is showing that ENLIGHT-DeepPT successfully predicts true responders in five independent patients' cohorts involving four different treatments spanning six cancer types with an overall odds ratio of 2.44, increasing the baseline response rate by 43.47% among predicted responders, without the need for any treatment data for training. Furthermore, its prediction accuracy on these datasets is comparable to a supervised approach predicting the response directly from the images, which needs to be trained and tested on the same cohort. ENLIGHT-DeepPT future application could provide clinicians with rapid treatment recommendations to an array of different therapies and importantly, may contribute to advancing precision oncology in developing countries.

Progesterone-mediated reversal of mifepristone-induced pregnancy termination in a rat model: an exploratory investigation.

Globally, a substantial proportion of pregnancies end in induced (particularly medication) abortion. However, data also indicates a percentage of women who seek assistance in potentially reversing the medication abortion process. While previous literature has suggested the potential for progesterone-mediated reversal of mifepristone-induced abortion, this process has not been effectively investigated pre-clinically. Our study explored the potential reversal of mifepristone-induced pregnancy termination using progesterone in a rat model, following a clear initiation of pregnancy termination. Female Long-Evans rats were divided into three groups (n = 10-16/group): Pregnant control (M-P-), mifepristone-only/pregnancy termination (M+P-) and mifepristone + progesterone (M+P+). Drug/vehicle administration occurred on day 12 of gestation (first-trimester human equivalent). Rat weight was measured throughout gestation. Uterine blood, collected post-drug/vehicle administration, was analyzed spectrophotometrically to measure blood loss. Additionally, at the end of gestation (day 21), ultrasound was utilized to confirm pregnancy and measure fetal heart rate. Number of gestational sacs, uterine weights and diameters were obtained following tissue collection. Our results indicate that progesterone administration following initiation of mifepristone-induced pregnancy termination (indicated by weight loss and uterine bleeding) reversed the process in 81% of rats in the M+P+ group. Following the initial weight loss, these rats proceeded to gain weight at a similar rate to the M-P- group, in contrast to the continued decrease displayed by the M+P- group (and unsuccessful reversals). Moreover, while uterine blood loss was similar to that of the M+P- group (confirming pregnancy termination initiation), number of gestational sacs, uterine weights, diameters, approximate fetal weights and fetal heart rates were similar to the M-P- group. Thus, our results indicate a clear progesterone-mediated reversal of an initiated mifepristone-induced pregnancy termination in a rat model at first-trimester human equivalent, with resultant fully developed living fetuses at the end of gestation, clearly indicating the necessity for further pre-clinical investigation to assist in better informing the scientific/medical communities of the potential implications in humans.

Comparison of tumor-informed and tumor-naïve sequencing assays for ctDNA detection in breast cancer.

Analysis of circulating tumor DNA (ctDNA) to monitor cancer dynamics and detect minimal residual disease has been an area of increasing interest. Multiple methods have been proposed but few studies have compared the performance of different approaches. Here, we compare detection of ctDNA in serial plasma samples from patients with breast cancer using different tumor-informed and tumor-naïve assays designed to detect structural variants (SVs), single nucleotide variants (SNVs), and/or somatic copy-number aberrations, by multiplex PCR, hybrid capture, and different depths of whole-genome sequencing. Our results demonstrate that the ctDNA dynamics and allele fractions (AFs) were highly concordant when analyzing the same patient samples using different assays. Tumor-informed assays showed the highest sensitivity for detection of ctDNA at low concentrations. Hybrid capture sequencing targeting between 1,347 and 7,491 tumor-identified mutations at high depth was the most sensitive assay, detecting ctDNA down to an AF of 0.00024% (2.4 parts per million, ppm). Multiplex PCR targeting 21-47 tumor-identified SVs per patient detected ctDNA down to 0.00047% AF (4.7 ppm) and has potential as a clinical assay.

Access to and Affordability of World Health Organization Essential Medicines for Cancer in Sub-Saharan Africa: Examples from Kenya, Rwanda, and Uganda.

BACKGROUND: Cancer mortality is high in sub-Saharan Africa (SSA), partly due to inadequate treatment access. We explored access to and affordability of cancer treatment regimens for the top 10 cancers utilizing examples from Kenya, Uganda, and Rwanda. MATERIALS AND METHODS: Population, healthcare financing, minimum wage, and cancer incidence and mortality data were obtained from the WHO, World Bank, public sources, and GLOBOCAN. National Essential Medicines List (NEML) alignment with 2019 WHO EML was assessed as a proportion. Cancer regimen pricing was calculated using public and proprietary sources and methods from prior studies. Affordability through universal healthcare coverage (UHC) was assessed as 1-year cost <3× gross national income per capita; and to patients out-of-pocket (OOP), as 30-day treatment course cost <1 day of minimum wage work. RESULTS: A total of 93.4% of the WHO EML cancer medicines were listed on the 2019 Kenya NEML, and 70.5% and 41.1% on Uganda (2016) and Rwanda (2015) NEMLs, respectively. Generic chemotherapies were available and affordable to governments through UHC to treat non-Hodgkin's lymphoma, cervical, breast, prostate, colorectal, ovarian cancers, and select leukemias. Newer targeted agents were not affordable through government UHC purchasing, while some capecitabine-based regimens were not affordable in Uganda and Rwanda. All therapies were not affordable OOP. CONCLUSION: All cancer treatment regimens were not affordable OOP and some were not covered by governments. Newer targeted drugs were not affordable to all 3 governments. UHC of cancer drugs and improving targeted therapy affordability to LMIC governments in SSA are key to improving treatment access and health outcomes.

AACR Project GENIE: 100,000 Cases and Beyond.

The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, the milestone GENIE 9.1-public release contains data from >110,000 tumors from >100,000 people treated at 19 cancer centers from the United States, Canada, the United Kingdom, France, the Netherlands, and Spain. Here, we demonstrate the use of these real-world data, harmonized through a centralized data resource, to accurately predict enrollment on genome-guided trials, discover driver alterations in rare tumors, and identify cancer types without actionable mutations that could benefit from comprehensive genomic analysis. The extensible data infrastructure and governance framework support additional deep patient phenotyping through biopharmaceutical collaborations and expansion to include new data types such as cell-free DNA sequencing. AACR Project GENIE continues to serve a global precision medicine knowledge base of increasing impact to inform clinical decision-making and bring together cancer researchers internationally. SIGNIFICANCE: AACR Project GENIE has now accrued data from >110,000 tumors, placing it among the largest repository of publicly available, clinically annotated genomic data in the world. GENIE has emerged as a powerful resource to evaluate genome-guided clinical trial design, uncover drivers of cancer subtypes, and inform real-world use of genomic data. This article is highlighted in the In This Issue feature, p. 2007.

Multi-omic machine learning predictor of breast cancer therapy response.

Breast cancers are complex ecosystems of malignant cells and the tumour microenvironment1. The composition of these tumour ecosystems and interactions within them contribute to responses to cytotoxic therapy2. Efforts to build response predictors have not incorporated this knowledge. We collected clinical, digital pathology, genomic and transcriptomic profiles of pre-treatment biopsies of breast tumours from 168 patients treated with chemotherapy with or without HER2 (encoded by ERBB2)-targeted therapy before surgery. Pathology end points (complete response or residual disease) at surgery3 were then correlated with multi-omic features in these diagnostic biopsies. Here we show that response to treatment is modulated by the pre-treated tumour ecosystem, and its multi-omics landscape can be integrated in predictive models using machine learning. The degree of residual disease following therapy is monotonically associated with pre-therapy features, including tumour mutational and copy number landscapes, tumour proliferation, immune infiltration and T cell dysfunction and exclusion. Combining these features into a multi-omic machine learning model predicted a pathological complete response in an external validation cohort (75 patients) with an area under the curve of 0.87. In conclusion, response to therapy is determined by the baseline characteristics of the totality of the tumour ecosystem captured through data integration and machine learning. This approach could be used to develop predictors for other cancers.

Residual cancer burden after neoadjuvant chemotherapy and long-term survival outcomes in breast cancer: a multicentre pooled analysis of 5161 patients.

BACKGROUND: Previous studies have independently validated the prognostic relevance of residual cancer burden (RCB) after neoadjuvant chemotherapy. We used results from several independent cohorts in a pooled patient-level analysis to evaluate the relationship of RCB with long-term prognosis across different phenotypic subtypes of breast cancer, to assess generalisability in a broad range of practice settings. METHODS: In this pooled analysis, 12 institutes and trials in Europe and the USA were identified by personal communications with site investigators. We obtained participant-level RCB results, and data on clinical and pathological stage, tumour subtype and grade, and treatment and follow-up in November, 2019, from patients (aged ≥18 years) with primary stage I-III breast cancer treated with neoadjuvant chemotherapy followed by surgery. We assessed the association between the continuous RCB score and the primary study outcome, event-free survival, using mixed-effects Cox models with the incorporation of random RCB and cohort effects to account for between-study heterogeneity, and stratification to account for differences in baseline hazard across cancer subtypes defined by hormone receptor status and HER2 status. The association was further evaluated within each breast cancer subtype in multivariable analyses incorporating random RCB and cohort effects and adjustments for age and pretreatment clinical T category, nodal status, and tumour grade. Kaplan-Meier estimates of event-free survival at 3, 5, and 10 years were computed for each RCB class within each subtype. FINDINGS: We analysed participant-level data from 5161 patients treated with neoadjuvant chemotherapy between Sept 12, 1994, and Feb 11, 2019. Median age was 49 years (IQR 20-80). 1164 event-free survival events occurred during follow-up (median follow-up 56 months [IQR 0-186]). RCB score was prognostic within each breast cancer subtype, with higher RCB score significantly associated with worse event-free survival. The univariable hazard ratio (HR) associated with one unit increase in RCB ranged from 1·55 (95% CI 1·41-1·71) for hormone receptor-positive, HER2-negative patients to 2·16 (1·79-2·61) for the hormone receptor-negative, HER2-positive group (with or without HER2-targeted therapy; p<0·0001 for all subtypes). RCB score remained prognostic for event-free survival in multivariable models adjusted for age, grade, T category, and nodal status at baseline: the adjusted HR ranged from 1·52 (1·36-1·69) in the hormone receptor-positive, HER2-negative group to 2·09 (1·73-2·53) in the hormone receptor-negative, HER2-positive group (p<0·0001 for all subtypes). INTERPRETATION: RCB score and class were independently prognostic in all subtypes of breast cancer, and generalisable to multiple practice settings. Although variability in hormone receptor subtype definitions and treatment across patients are likely to affect prognostic performance, the association we observed between RCB and a patient's residual risk suggests that prospective evaluation of RCB could be considered to become part of standard pathology reporting after neoadjuvant therapy. FUNDING: National Cancer Institute at the US National Institutes of Health.

DNA methylation landscapes of 1538 breast cancers reveal a replication-linked clock, epigenomic instability and cis-regulation.

DNA methylation is aberrant in cancer, but the dynamics, regulatory role and clinical implications of such epigenetic changes are still poorly understood. Here, reduced representation bisulfite sequencing (RRBS) profiles of 1538 breast tumors and 244 normal breast tissues from the METABRIC cohort are reported, facilitating detailed analysis of DNA methylation within a rich context of genomic, transcriptional, and clinical data. Tumor methylation from immune and stromal signatures are deconvoluted leading to the discovery of a tumor replication-linked clock with genome-wide methylation loss in non-CpG island sites. Unexpectedly, methylation in most tumor CpG islands follows two replication-independent processes of gain (MG) or loss (ML) that we term epigenomic instability. Epigenomic instability is correlated with tumor grade and stage, TP53 mutations and poorer prognosis. After controlling for these global trans-acting trends, as well as for X-linked dosage compensation effects, cis-specific methylation and expression correlations are uncovered at hundreds of promoters and over a thousand distal elements. Some of these targeted known tumor suppressors and oncogenes. In conclusion, this study demonstrates that global epigenetic instability can erode cancer methylomes and expose them to localized methylation aberrations in-cis resulting in transcriptional changes seen in tumors.

The temporal mutational and immune tumour microenvironment remodelling of HER2-negative primary breast cancers.

The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R2 = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R2 = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.

Compensation Strategies for Bioelectric Signal Changes in Chronic Selective Nerve Cuff Recordings: A Simulation Study.

Peripheral nerve interfaces (PNIs) allow us to extract motor, sensory, and autonomic information from the nervous system and use it as control signals in neuroprosthetic and neuromodulation applications. Recent efforts have aimed to improve the recording selectivity of PNIs, including by using spatiotemporal patterns from multi-contact nerve cuff electrodes as input to a convolutional neural network (CNN). Before such a methodology can be translated to humans, its performance in chronic implantation scenarios must be evaluated. In this simulation study, approaches were evaluated for maintaining selective recording performance in the presence of two chronic implantation challenges: the growth of encapsulation tissue and rotation of the nerve cuff electrode. Performance over time was examined in three conditions: training the CNN at baseline only, supervised re-training with explicitly labeled data at periodic intervals, and a semi-supervised self-learning approach. This study demonstrated that a selective recording algorithm trained at baseline will likely fail over time due to changes in signal characteristics resulting from the chronic challenges. Results further showed that periodically recalibrating the selective recording algorithm could maintain its performance over time, and that a self-learning approach has the potential to reduce the frequency of recalibration.

The Impact of COVID-19 and Associated Interventions on Mental Health: A Cross-Sectional Study in a Sample of University Students.

BACKGROUND: Mental health issues have continued to rise globally, including among university students. The COVID-19 pandemic has exacerbated the previously existing and concerning problem. Given that coping mechanisms have been proposed to mediate the relationship between stressors and mental health, the aim of our cross-sectional study was to investigate the mediation of coping mechanisms on the relationship between the impact of the COVID-19 pandemic and mental health. METHODS: University students (≥18 years old; N = 676; 31% male, 69% female) were administered an anonymous survey addressing current demographics, COVID-19 pandemic-related demographics, personal experiences, sources of stress and perceived effect on mental health, politics, sources of news/information, and various pre-validated scales addressing mental health (DASS-21), the impact of the COVID-19 pandemic (IES-R) and coping strategies utilized (Brief COPE). RESULTS: Our results indicate a substantial proportion of our sample reporting scores in the severe and extremely severe DASS-21 categories, in addition to ~50% reporting a perceived deterioration in mental health relative to pre-COVID-19 pandemic. Moreover, a substantial proportion of students reported IES-R scores at levels where PTSD is of clinical concern. Alarmingly, a significant proportion of females (~15%) reported scores reflecting potential long-term PTSD-related implications. Females tended to be more severely impacted in all mental health measures. Mediation analysis indicated that while dysfunctional coping mediated the relationship between the impact of the event (COVID-19 pandemic) and all three mental health outcomes, overall, this was not the case with the positive coping strategies. CONCLUSION: Our study appears to indicate a reduced buffering influence on negative mental health outcomes by the positive coping mechanisms investigated in relation to the COVID-19 pandemic and secondary interventions implemented. While the findings of this study pertain specifically to university students, they corroborate the existing extensive body of research (from physiological to behavioral, preclinical to clinical) pertaining to the response associated with major stressful events at every level of society. In this regard, the findings imply the necessity for health and other authorities, tasked with safeguarding public well-being, to avoid reactive interventions that do not appropriately balance the risks and benefits, potentially exacerbating pre-existing psychopathologies and compromising social order.

Pregnancy-induced long-term uterine vascular remodeling in the rat.

Despite the available research investigating uterine physiology during and immediately following pregnancy, including at the vascular and muscular levels, knowledge of the potential long-term timeline of such changes is limited. Thus, our study sought to investigate the potential long-term changes in uterine vasculature and horn length in the postpartum rat, following delivery and weaning. Female Long-Evans rats (n = 9-11 rats/group/timepoint) were divided into two groups: a pregnant group and an age-matched virgin control group. Rat weight, food consumption and vaginal impedance measurements were recorded throughout the experiment. Rats in the pregnant group were bred and pregnancy was confirmed using ultrasound imaging. The uterus and its vasculature were collected at various timepoints following weaning: 3 (week of weaning), 8-9 and 13 weeks postpartum, and at age-equivalent timepoints in the virgin group, and the diameters of the main uterine artery and vein, and lengths of the mesometrial segmental vessels (MSV) and uterine horns were recorded. The results indicated a significant difference between the previously-pregnant and virgin rats in both internal and external arterial diameters (but not arterial wall thickness), as well as the uterine horn length, 3 weeks postpartum, but not 8-9 and 13 weeks postpartum. Significant differences were observed in both venous diameter and MSV length at all timepoints measured. Placental scars were also observed in previously-pregnant rats at all timepoints measured. Our study highlights the long-term impact of pregnancy on the uterine vasculature and the necessity for consideration of such changes on subsequent pregnancies, as well as pregnancy-related vascular pathologies.

The molecular landscape of Asian breast cancers reveals clinically relevant population-specific differences.

Molecular profiling of breast cancer has enabled the development of more robust molecular prognostic signatures and therapeutic options for breast cancer patients. However, non-Caucasian populations remain understudied. Here, we present the mutational, transcriptional, and copy number profiles of 560 Malaysian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to breast tumours in Caucasian women, we show an increased prevalence of HER2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. We also observe elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst HER2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

Impact of Encapsulation Tissue Growth on Selective Recording in Nerve Cuff Electrodes: A Simulation Study.

Peripheral nerve interfaces (PNIs) allow us to extract motor, sensory and autonomic information from the nervous system and use it as control signals in neuroprosthetic and neuromodulation systems. Recent efforts have aimed to improve the recording selectivity of PNIs, including by using spatiotemporal patterns from multi-contact nerve cuff electrodes as input to a convolutional neural network (CNN). Before such a methodology can be translated to humans, its performance in chronic implantation scenarios must be evaluated. We investigated the performance of a CNN-based selective recording approach in the presence of encapsulation tissue, a common immune response to the implantation of a neural interface. This factor was simulated using anatomically accurate computational models of a rat sciatic nerve and nerve cuff electrode. Performance over time was examined in three conditions: training the CNN at baseline only, supervised retraining with explicitly labeled data at periodic intervals, and a semi-supervised self-learning approach. The periodic recalibration approach demonstrated the best results, with an average F1-score of 0.96 ± 0.04, 0.89 ± 0.08, and 0.80 ± 0.08 for SNRs of -5 dB, -10 dB, and -15 dB, respectively, across all time points. Thus, the periodic recalibration approach may be an effective solution to compensate for changes in signal recordings seen over time as a result of encapsulation tissue. The self-learning approach, in which a network is retrained periodically using predicted labels, generally showed degradation in classification performance over time, even as the frequency of training was increased, attributed to an eventual accumulation of mislabeled training data.

Compulsive Internet Pornography Use and Mental Health: A Cross-Sectional Study in a Sample of University Students in the United States.

BACKGROUND: The sustained rise in negative mental health reports among university students is a source of continued global concern, and investigation continues into potential contributors to this rise. This includes the increased prevalence of risky sexual behaviors. Related is the increased prevalence of pornography use. Our study sought to explore the potential relationship between compulsive use of pornography and mental health in university students. METHODS: Our sample consisted of university students (N = 1031; 34% male, 66% female) from Franciscan University of Steubenville, Steubenville, Ohio. An anonymous survey was sent to all students at the university over the age of 18. The survey was comprised of the following: (1) demographic questions, (2) questions on pornography use and perception, (3) a modified version of the Compulsive Internet Use Scale (mCIUS) assessing various factors associated with compulsive internet pornography use, (4) questions assessing emotional and sexual states relative to pornography use (EmSS), and (5) the 21-question version of the Depression, Anxiety and Stress Scale (DASS-21). RESULTS: Our results indicate that 56.6% of those surveyed reported lifetime pornography use, with a significantly higher proportion of males than females reporting such use. The majority of students reported accessing pornography through internet-related technologies. Additionally, 17.0, 20.4, and 13.5% of students reported severe or extremely severe levels of depression, anxiety and stress, respectively, with compulsive pornography use significantly affecting all three mental health parameters in both sexes. Exploratory Factor Analysis identified three factors suggesting emotional coping, dependence and preoccupation for the mCIUS items and three factors reflecting interoceptive, impotent, and extrinsic characteristics for the EmSS items. Regression analysis indicated that various demographics, items pertaining to reduced control and social impairment, and other variables pertaining to pornography use predicted mental health outcomes. Faith, morals and personal motivation were the primary variables reported to help reduce pornography use. CONCLUSION: Our analyses indicate a significant relationship between mental health and pornography use, including behaviors reflecting behavioral addictions, highlighting the necessity for a better understanding and consideration of the potential contribution of internet pornography to negative mental health among university students.

Personalized circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer.

Longitudinal analysis of circulating tumor DNA (ctDNA) has shown promise for monitoring treatment response. However, most current methods lack adequate sensitivity for residual disease detection during or after completion of treatment in patients with nonmetastatic cancer. To address this gap and to improve sensitivity for minute quantities of residual tumor DNA in plasma, we have developed targeted digital sequencing (TARDIS) for multiplexed analysis of patient-specific cancer mutations. In reference samples, by simultaneously analyzing 8 to 16 known mutations, TARDIS achieved 91 and 53% sensitivity at mutant allele fractions (AFs) of 3 in 104 and 3 in 105, respectively, with 96% specificity, using input DNA equivalent to a single tube of blood. We successfully analyzed up to 115 mutations per patient in 80 plasma samples from 33 women with stage I to III breast cancer. Before treatment, TARDIS detected ctDNA in all patients with 0.11% median AF. After completion of neoadjuvant therapy, ctDNA concentrations were lower in patients who achieved pathological complete response (pathCR) compared to patients with residual disease (median AFs, 0.003 and 0.017%, respectively, P = 0.0057, AUC = 0.83). In addition, patients with pathCR showed a larger decrease in ctDNA concentrations during neoadjuvant therapy. These results demonstrate high accuracy for assessment of molecular response and residual disease during neoadjuvant therapy using ctDNA analysis. TARDIS has achieved up to 100-fold improvement beyond the current limit of ctDNA detection using clinically relevant blood volumes, demonstrating that personalized ctDNA tracking could enable individualized clinical management of patients with cancer treated with curative intent.

Biological, Behavioral and Physiological Consequences of Drug-Induced Pregnancy Termination at First-Trimester Human Equivalent in an Animal Model.

Given the significant physiological changes that take place during and resulting from pregnancy, as well as the relative absence of such information in relation to pregnancy termination, this study investigated the potential for developing a valid animal model to objectively assess the biological, physiological and behavioral consequences of drug-induced pregnancy termination. Female Long-Evans rats were divided into four groups (n = 19-21/group), controlling for drug [mifepristone (50 mg/kg/3 ml, i.g.)/misoprostol (0.3 mg/kg/ml, i.g.) or vehicle (1% Carboxymethylcellulose Sodium/0.2% Tween® 80 suspension, i.g.)] and pregnancy. Drug administration took place on days 12-14 of gestation (days 28-40 human gestational equivalent). Vehicle was administered to the controls on the same days. Parameters measured included rat body weight, food intake, vaginal impedance, sucrose consumption/preference, locomotor activity, forced swim test, and home-cage activity. At the termination of the study, rats were deeply anesthetized using urethane, and blood, brain, and liver were collected for biochemical analysis. Following drug/vehicle administration, only the pregnancy termination group (pregnant, drug) displayed a significant decrease in body weight, food intake, locomotor activity-related behaviors and home-cage activity relative to the control group (non-pregnant, vehicle). Additionally, the pregnancy termination group was the only group that displayed a significant reduction in sucrose consumption/preference during Treatment Week relative to Pre-Treatment Week. Vaginal impedance did not significantly decrease over time in parous rats in contrast to all other groups, including the rats in the pregnancy termination group. Biochemical analysis indicated putative drug- and pregnancy-specific influences on oxidative balance. Regression analysis indicated that pregnancy termination was a predictor variable for body weight, food intake and all locomotor activity parameters measured. Moreover, pertaining to body weight and food intake, the pregnancy termination group displayed significant changes, which were not present in a group of naturally miscarrying rats following pregnancy loss. Overall, our results appear to suggest negative biological and behavioral effects following pregnancy termination, that appear to also be distinct from natural miscarriage, and potential benefits of parity pertaining to fecundity. Thus, our findings indicate the importance for further objective investigation of the physiological and behavioral consequences of medical abortion, in order to provide further insight into the potential implications in humans.

The Genomic and Immune Landscapes of Lethal Metastatic Breast Cancer.

The detailed molecular characterization of lethal cancers is a prerequisite to understanding resistance to therapy and escape from cancer immunoediting. We performed extensive multi-platform profiling of multi-regional metastases in autopsies from 10 patients with therapy-resistant breast cancer. The integrated genomic and immune landscapes show that metastases propagate and evolve as communities of clones, reveal their predicted neo-antigen landscapes, and show that they can accumulate HLA loss of heterozygosity (LOH). The data further identify variable tumor microenvironments and reveal, through analyses of T cell receptor repertoires, that adaptive immune responses appear to co-evolve with the metastatic genomes. These findings reveal in fine detail the landscapes of lethal metastatic breast cancer.