Polycyclic Aromatic Hydrocarbons and Pancreatic Cancer: An Analysis of the Blood Biomarker, r-1,t-2,3,c-4-Tetrahydroxy-1,2,3,4-tetrahydrophenanthrene and Selected Metabolism Gene SNPs.

Exposure to polycyclic aromatic hydrocarbons (PAHs), byproducts of incomplete combustion, and their effects on the development of cancer are still being evaluated. Recent studies have analyzed the relationship between PAHs and tobacco or dietary intake in the form of processed foods and smoked/well-done meats. This study aims to assess the association of a blood biomarker and metabolite of PAHs, r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene (PheT), dietary intake, selected metabolism SNPs, and pancreatic cancer. Demographics, food-frequency data, SNPs, treatment history, and levels of PheT in plasma were determined from 400 participants (202 cases and 198 controls) and evaluated based on pancreatic adenocarcinoma diagnosis. Demographic and dietary variables were selected based on previously published literature indicating association with pancreatic cancer. A multiple regression model combined the significant demographic and food items with SNPs. Final multivariate logistic regression significant factors (p-value < 0.05) associated with pancreatic cancer included: Type 2 Diabetes [OR = 6.26 (95% CI = 2.83, 14.46)], PheT [1.03 (1.02, 1.05)], very well-done red meat [0.90 (0.83, 0.96)], fruit/vegetable servings [1.35 (1.06, 1.73)], recessive (rs12203582) [4.11 (1.77, 9.91)], recessive (rs56679) [0.2 (0.06, 0.85)], overdominant (rs3784605) [3.14 (1.69, 6.01)], and overdominant (rs721430) [0.39 (0.19, 0.76)]. Of note, by design, the level of smoking did not differ between our cases and controls. This study does not provide strong evidence that PheT is a biomarker of pancreatic cancer susceptibility independent of dietary intake and select metabolism SNPs among a nonsmoking population.

Observations of COVID-19 vaccine coverage and vaccine hesitancy on COVID-19 outbreak: An American ecological study.

In this ecological study, we aim to establish the role vaccines play in bringing the pandemic under control, as well as the impact of pathogen variants, vaccine hesitancy, and medical resource availability during the process by utilizing publicly available data. The study spans a three-year data collection period for daily hospital admissions due to COVID-19 and the daily reported cases of COVID-19 across all 50 states in the USA. In doing so, we aim to demonstrate the difference in severity of the SARS-CoV-2 pathogen among vaccinated and unvaccinated populations in the USA. The study assesses the correlation of COVID-19 vaccines (e.g., Pfizer, Moderna, and Janssen) and disease outcomes (transmissibility, severity, and deaths) caused by different strains of SARS-CoV-2 and establishes a negative correlation between COVID-19 vaccine and disease outcomes. By considering potential confounders in vaccine hesitancy, medical resource availability and vaccine dosage, we demonstrate the aforementioned to be insubstantial in predicting disease outcomes while the latter displays a contrasting significance in terms of disease outcomes. Between all the major variants of concern, the Delta and Omicron variants in particular have been associated with higher virulence and transmissibility factors respectively. Hence, the CDC continues to encourage the US population to get vaccinated since vaccines are one of the most effective ways to protect the community from potential outbreaks and prevent severe disease manifestations.

Application of Feature Selection and Deep Learning for Cancer Prediction Using DNA Methylation Markers.

DNA methylation is a process that can affect gene accessibility and therefore gene expression. In this study, a machine learning pipeline is proposed for the prediction of breast cancer and the identification of significant genes that contribute to the prediction. The current study utilized breast cancer methylation data from The Cancer Genome Atlas (TCGA), specifically the TCGA-BRCA dataset. Feature engineering techniques have been utilized to reduce data volume and make deep learning scalable. A comparative analysis of the proposed approach on Illumina 27K and 450K methylation data reveals that deep learning methodologies for cancer prediction can be coupled with feature selection models to enhance prediction accuracy. Prediction using 450K methylation markers can be accomplished in less than 13 s with an accuracy of 98.75%. Of the list of 685 genes in the feature selected 27K dataset, 578 were mapped to Ensemble Gene IDs. This reduced set was significantly (FDR < 0.05) enriched in five biological processes and one molecular function. Of the list of 1572 genes in the feature selected 450K data set, 1290 were mapped to Ensemble Gene IDs. This reduced set was significantly (FDR < 0.05) enriched in 95 biological processes and 17 molecular functions. Seven oncogene/tumor suppressor genes were common between the 27K and 450K feature selected gene sets. These genes were RTN4IP1, MYO18B, ANP32A, BRF1, SETBP1, NTRK1, and IGF2R. Our bioinformatics deep learning workflow, incorporating imputation and data balancing methods, is able to identify important methylation markers related to functionally important genes in breast cancer with high accuracy compared to deep learning or statistical models alone.

A Pilot Study of Blood-Based Methylation Markers Associated With Pancreatic Cancer.

Over the past several decades in the United States, incidence of pancreatic cancer (PCa) has increased, with the 5-year survival rate remaining extremely low at 10.8%. Typically, PCa is diagnosed at an advanced stage, with the consequence that there is more tumor heterogeneity and increased probability that more cells are resistant to treatments. Risk factors for PCa can serve as a way to select a high-risk population and develop biomarkers to improve early detection and treatment. We focus on blood-based methylation as an approach to identify a marker set that can be obtained in a minimally invasive way (through peripheral blood) and could be applied to a high-risk subpopulation [those with recent onset type 2 diabetes (DM)]. Blood samples were collected from 30 patients, 15 had been diagnosed with PCa and 15 had been diagnosed with recent onset DM. HumanMethylationEPIC Beadchip (Illumina, CA, United States) was used to quantify methylation of approximately 850,000 methylation sites across the genome and to analyze methylation markers associated with PCa or DM or both. Exploratory analysis conducted to propose importance of top CpG (5'-C-phosphate-G-3') methylation site associated genes and visualized using boxplots. A methylation-based age predictor was also investigated for ability to distinguish disease groups from controls. No methylation markers were observed to be significantly associated with PCa or new onset diabetes compared with control the respective control groups. In our exploratory analysis, one methylation marker, CpG04969764, found in the Laminin Subunit Alpha 5 (LAMA5) gene region was observed in both PCa and DM Top 100 methylation marker sets. Modification of LAMA5 methylation or LAMA5 gene function may be a way to distinguish those recent DM cases with and without PCa, however, additional studies with larger sample sizes and different study types (e.g., cohort) will be needed to test this hypothesis.

Evaluating the Association of Face Covering Mandates on COVID-19 Severity by State.

OBJECTIVE: During the COVID-19 pandemic in the United States, mitigation measures were implemented on a state-by-state basis. Governors were responsible for establishing interventions appropriate for their states and the timing of implementation. This paper evaluated the association between the presence and timing of a mask mandate and the severity of the COVID-19 epidemic by state. METHODS: The states were divided into 3 categories based on when the governors of each state implemented a mask mandate: Early (mask mandate implemented between March 2020 and June 2020), Late (July 2020-December 2020), and Never (no mask mandate implemented). The rates of hospitalizations and mortality (per 100 000) were assessed at the different time points during the pandemic across these categories from March to December 2020. RESULTS: The mortality rates across all 3 groups were observed to be highest in the beginning and toward the end of the pandemic in 2020 with the peak observed in the Early group between April and May 2020. Also, the rates of hospitalization increased steadily across all groups. The Early mask group was comprised of 86.7% and 13.3% states with Democratic and Republican governors respectively, and no states in the Never category had Democratic governors. CONCLUSION: These results support the benefit of implementing a mask mandate to minimize the impact of the COVID-19 pandemic and the role of political affiliation of governors on that impact.

Epidemiology of Hepatitis C virus infection among incarcerated populations in North Dakota.

This retrospective cohort study was conducted to determine the prevalence of HCV infections among individuals incarcerated in a state prison system and identify potential contributing factors to HCV infection. North Dakota Department of Corrections and Rehabilitation (NDDOCR) data from 2009 to 2018 was used and period prevalence was calculated for this 10-year time period. The period prevalence of HCV infection was (15.13% (95% CI 14.39-15.90) with a marginally significant (p-value: 0.0542) increasing linear trend in annual prevalence over this period. Multivariate logistic regression analysis was used to identify risk factors associated with HCV infection. The main significant independent risk factors for HCV infection in this incarcerated population were age >40 years [OR: 1.78 (1.37-2.32)]; sex [OR: 1.21 (1.03-1.43)]; race/ethnicity [OR: 1.97 (1.69-2.29)]; history of intravenous drug use (IVDU) [OR: 7.36 (6.41-8.44)]; history of needle or syringe sharing [OR: 7.57 (6.62-8.67)]; and alcohol use [OR: 0.87 (0.77-0.99)]. Study limitations include uncollected information on sexual history, frequency or duration of injection drug use and blood transfusion history of the incarcerated population. Considering the high prevalence of HCV infection and its associated risk factors, it is important to implement prevention programs such as syringe/needle exchanges and counsel with imprisoned IVD users.

Methods and Techniques to Facilitate the Development of Clostridium novyi NT as an Effective, Therapeutic Oncolytic Bacteria.

The tumor microenvironment is characterized by anomalous vascularization, hypoxia, and acidity at the core of solid tumors that culminates in concentrated necrosis and immune system dysregulation among other effects. While this environment presents several challenges for the development of oncotherapeutics that deliver their activity via the enhanced permeability and retention (EPR) effect of the leaky blood vessels around a tumor, oncolytic bacteria, or a class of bacteria with a noted capacity to lyse solid tumors, are attracted to the very environment found at the center of solid tumors that confounds other therapeutics. It is this capacity that allows for a potent, active penetration from the tumor margins into the core, and subsequent colonization to facilitate lysis and immune reactivation. Clostridium novyi in particular has recently shown great promise in preclinical and clinical trials when administered directly to the tumor. These studies indicate that C. novyi is uniquely poised to effectively accomplish the long sought after "holy grail" of oncotherapeutics: selective tumor localization via intravenous delivery. This study reports the development of efficient methods that facilitate experimental work and therapeutic translation of C. novyi including the ability to work with this obligate micro-anaerobe on the benchtop. Additionally, this study seeks to utilize this newfound experimental flexibility to address several gaps in the current knowledge regarding the efficacy of CRIPSR/Cas9-mediated gene insertion in this species to further develop this oncolytic bacteria and the genetic customization of bacteria in general.

Associations between oil development and sexually transmitted infections: Public health nurse perspectives.

BACKGROUND: Oil development (OD) has been associated with increased sexually transmitted infection (STI) rates, with limited focus on the North Dakota (ND) oil boom. Public health (PH) nurse experiences can provide context related to health challenges during OD-related population booms. OBJECTIVE: To compare reported STI rates in ND oil-producing (OP) and non-oil-producing (NOP) counties before, during, and after the oil boom and describe PH nurse experiences during this time. DESIGN: We conducted secondary data analysis of oil production data and reported rates for chlamydia and gonorrhea, and conducted interviews with ND PH nurses. SAMPLE: PH nurses within ND counties geographically located in or near OD in the state. MEASUREMENTS: ND county-level OD data trends were compared to similarly timed reported rates of chlamydia and gonorrhea in OP and NOP counties. PH nurse interviews were conducted addressing their STI-related experiences working in PH during the oil boom. RESULTS: Significant findings include a correlation between OD and gonorrhea rates. PH nurses described a limited PH infrastructure to meet the health needs of a transient, increasing population. CONCLUSIONS: Expanding the role of PH nurses in ND to implement STI screening and treatment would improve access to STI testing allowing for comprehensive reporting of STIs.

Perspectives on Triple-Negative Breast Cancer: Current Treatment Strategies, Unmet Needs, and Potential Targets for Future Therapies.

Triple-negative breast cancer (TNBC), characterized by the absence or low expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2), is the most aggressive subtype of breast cancer. TNBC accounts for about 15% of breast cancer cases in the U.S., and is known for high relapse rates and poor overall survival (OS). Chemo-resistant TNBC is a genetically diverse, highly heterogeneous, and rapidly evolving disease that challenges our ability to individualize treatment for incomplete responders and relapsed patients. Currently, the frontline standard chemotherapy, composed of anthracyclines, alkylating agents, and taxanes, is commonly used to treat high-risk and locally advanced TNBC. Several FDA-approved drugs that target programmed cell death protein-1 (Keytruda) and programmed death ligand-1 (Tecentriq), poly ADP-ribose polymerase (PARP), and/or antibody drug conjugates (Trodelvy) have shown promise in improving clinical outcomes for a subset of TNBC. These inhibitors that target key genetic mutations and specific molecular signaling pathways that drive malignant tumor growth have been used as single agents and/or in combination with standard chemotherapy regimens. Here, we review the current TNBC treatment options, unmet clinical needs, and actionable drug targets, including epidermal growth factor (EGFR), vascular endothelial growth factor (VEGF), androgen receptor (AR), estrogen receptor beta (ERß), phosphoinositide-3 kinase (PI3K), mammalian target of rapamycin (mTOR), and protein kinase B (PKB or AKT) activation in TNBC. Supported by strong evidence in developmental, evolutionary, and cancer biology, we propose that the K-RAS/SIAH pathway activation is a major tumor driver, and SIAH is a new drug target, a therapy-responsive prognostic biomarker, and a major tumor vulnerability in TNBC. Since persistent K-RAS/SIAH/EGFR pathway activation endows TNBC tumor cells with chemo-resistance, aggressive dissemination, and early relapse, we hope to design an anti-SIAH-centered anti-K-RAS/EGFR targeted therapy as a novel therapeutic strategy to control and eradicate incurable TNBC in the future.

Unmet Clinical Need: Developing Prognostic Biomarkers and Precision Medicine to Forecast Early Tumor Relapse, Detect Chemo-Resistance and Improve Overall Survival in High-Risk Breast Cancer.

Chemo-resistant breast cancer is a major barrier to curative treatment for a significant number of women with breast cancer. Neoadjuvant chemotherapy (NACT) is standard first- line treatment for most women diagnosed with high-risk TNBC, HER2+, and locally advanced ER+ breast cancer. Current clinical prognostic tools evaluate four clinicopathological factors: Tumor size, LN status, pathological stage, and tumor molecular subtype. However, many similarly treated patients with identical residual cancer burden (RCB) following NACT experience distinctly different tumor relapse rates, clinical outcomes and survival. This problem is particularly apparent for incomplete responders with a high-risk RCB classification following NACT. Therefore, there is a pressing need to identify new prognostic and predictive biomarkers, and develop novel curative therapies to augment current standard of care (SOC) treatment regimens to save more lives. Here, we will discuss these unmet needs and clinical challenges that stand in the way of precision medicine and personalized cancer therapy.

Ripple Effects of the Communities Preventing Childhood Obesity Project.

This research examines the practice of community coaching within coalitions in the Communities Preventing Childhood Obesity project. A quasi-experimental design was used in seven Midwestern states. Each state selected two rural, low-income communities with functioning health coalitions. Coalitions were randomly assigned to be intervention or comparison communities. After 4 years of the coaching intervention, ripple effect mapping served as one method for examining the coalitions' work that may affect children's weight status. A research team from each state conducted ripple effect mapping with their two coalitions, resulting in 14 ripple maps. Community capitals framework and the social-ecological model were used for coding the items identified within the ripple maps. A quantitative scoring analysis determined if differences existed between the intervention and comparison coalitions in terms of the activities, programs, funding, and partnerships for social-ecological model score (e.g., individual, community, policy levels), community capitals score, and ripples score (e.g., number of branches formed within the maps). All scores were higher in intervention communities; however, the differences were not statistically significant (p > .05). Assessing community assets, such as availability of a community coach, is necessary in order to decide whether to deploy certain resources when designing health promotion strategies.

Resurgence of Syphilis in the United States: An Assessment of Contributing Factors.

In the last decade, there has been a marked resurgence of syphilis in the United States despite the availability of effective treatments and previously reliable prevention strategies. The majority of cases are among the population of men who have sex with men (MSM); however, there has also been a recent increase among premenopausal women, coinciding with a concerning rise of congenital cases. The resurgence of syphilis can be largely attributed to changing social and behavioral factors, especially among young MSM. The biological association of syphilis with human immunodeficiency virus (HIV) transmission and acquisition is particularly alarming because of the increased individual and healthcare burden. In addition, some individual actions and public health efforts that are meant to reduce the risk of acquiring HIV may actually lead to risk compensation that facilitates the transmission of syphilis. Untreated syphilis is associated with detrimental health outcomes; therefore, both effective prevention strategies and treatment of this systemic disease have important short-term and long-term public health implications. This article offers a review of social and behavioral factors contributing to the current resurgence and recommendations for reducing syphilis incidence through medical and public health prevention strategies.

Epigenomics of Pancreatic Cancer: A Critical Role for Epigenome-Wide Studies.

Several challenges present themselves when discussing current approaches to the prevention or treatment of pancreatic cancer. Up to 45% of the risk of pancreatic cancer is attributed to unknown causes, making effective prevention programs difficult to design. The most common type of pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC), is generally diagnosed at a late stage, leading to a poor prognosis and 5-year survival estimate. PDAC tumors are heterogeneous, leading to many identified cell subtypes within one patient's primary tumor. This explains why there is a high frequency of tumors that are resistant to standard treatments, leading to high relapse rates. This review will discuss how epigenetic technologies and epigenome-wide association studies have been used to address some of these challenges and the future promises these approaches hold.

The effect of age on DNA methylation in whole blood among Bangladeshi men and women.

BACKGROUND: It is well-known that methylation changes occur as humans age, however, understanding how age-related changes in DNA methylation vary by sex is lacking. In this study, we characterize the effect of age on DNA methylation in a sex-specific manner and determine if these effects vary by genomic context. We used the Illumina HumanMethylation 450 K array and DNA derived from whole blood for 400 adult participants (189 males and 211 females) from Bangladesh to identify age-associated CpG sites and regions and characterize the location of these age-associated sites with respect to CpG islands (vs. shore, shelf, or open sea) and gene regions (vs. intergenic). We conducted a genome-wide search for age-associated CpG sites (among 423,604 sites) using a reference-free approach to adjust for cell type composition (the R package RefFreeEWAS) and performed an independent replication analysis of age-associated CpGs. RESULTS: The number of age-associated CpGs (p < 5 x 10- 8) were 986 among men and 3479 among women of which 2027(63.8%) and 572 (64.1%) replicated (using Bonferroni adjusted p < 1.2 × 10- 5). For both sexes, age-associated CpG sites were more likely to be hyper-methylated with increasing age (compared to hypo-methylated) and were enriched in CpG islands and promoter regions compared with other locations and all CpGs on the array. Although we observed strong correlation between chronological age and previously-developed epigenetic age models (r ≈ 0.8), among our top (based on lowest p-value) age-associated CpG sites only 12 for males and 44 for females are included in these prediction models, and the median chronological age compared to predicted age was 44 vs. 51.7 in males and 45 vs. 52.1 in females. CONCLUSIONS: Our results describe genome-wide features of age-related changes in DNA methylation. The observed associations between age and methylation were generally consistent for both sexes, although the associations tended to be stronger among women. Our population may have unique age-related methylation changes that are not captured in the established methylation-based age prediction model we used, which was developed to be non-tissue-specific.

A mathematical model of case-ascertainment bias: Applied to case-control studies nested within a randomized screening trial.

When some individuals are screen-detected before the beginning of the study, but otherwise would have been diagnosed symptomatically during the study, this results in different case-ascertainment probabilities among screened and unscreened participants, referred to here as lead-time-biased case-ascertainment (LTBCA). In fact, this issue can arise even in risk-factor studies nested within a randomized screening trial; even though the screening intervention is randomly allocated to trial arms, there is no randomization to potential risk-factors and uptake of screening can differ by risk-factor strata. Under the assumptions that neither screening nor the risk factor affects underlying incidence and no other forms of bias operate, we simulate and compare the underlying cumulative incidence and that observed in the study due to LTBCA. The example used will be constructed from the randomized Prostate, Lung, Colorectal, and Ovarian cancer screening trial. The derived mathematical model is applied to simulating two nested studies to evaluate the potential for screening bias in observational lung cancer studies. Because of differential screening under plausible assumptions about preclinical incidence and duration, the simulations presented here show that LTBCA due to chest x-ray screening can significantly increase the estimated risk of lung cancer due to smoking by 1% and 50%. Traditional adjustment methods cannot account for this bias, as the influence screening has on observational study estimates involves events outside of the study observation window (enrollment and follow-up) that change eligibility for potential participants, thus biasing case ascertainment.

Enforcement Associated With Higher School-Reported Immunization Rates.

INTRODUCTION: North Dakota's school-reported kindergarten immunization rates were among the lowest in the U.S. during the 2015-2016 school year. Ninety percent of kindergartners were fully immunized in accordance with state requirements, 3% had an exemption, and as many as 7% were noncompliant. School enforcement of immunization requirements has been noted as variable. This study sought to better understand the relationship between school-reported immunization rates and the enforcement of immunization requirements. METHODS: Kindergarten immunization rates were compared between schools annually enforcing immunization requirements to the point of excluding noncompliant children and schools not enforcing. In addition, immunization rates were assessed after an educational intervention that led some school districts to change their enforcement policies during the 2015-2016 school year. Analyses were completed in 2016 and 2017. RESULTS: Kindergarten immunization rates were significantly higher in schools that annually enforced compared with schools that did not enforce (p≤0.001, all vaccines; difference between means: diphtheria-tetanus-attenuated pertussis=7.5% [95% CI=3.9%, 11.1%]; polio=6.2% [95% CI=3.3%, 9.1%]; measles, mumps, and rubella=7% [95% CI=3.5%, 10.5%]; hepatitis B=3.7% [95% CI=1.5%, 5.9%]; and varicella=6.9% [95% CI=3.4%, 10.4%]). School districts that began enforcing saw a significant increase in vaccination rates (diphtheria-tetanus-attenuated pertussis=6% [95% CI=2%, 11%] and measles, mumps, and rubella=7% [95% CI=3%, 11%]). Enforcement in newly enforcing districts led to a large decrease in the number of noncompliant students and did not lead to significant increases in exemption rates. CONCLUSIONS: In North Dakota, lack of school enforcement is strongly associated with lower immunization rates and a large noncompliant population. Addressing noncompliance through school enforcement could significantly increase school-reported immunization rates.

Association between Alcohol Consumption, Folate Intake, and Risk of Pancreatic Cancer: A Case-Control Study.

Pancreatic cancer is one of the most fatal common cancers affecting both men and women, representing about 3% of all new cancer cases in the United States. In this study, we aimed to investigate the association of pancreatic cancer risk with alcohol consumption as well as folate intake. We performed a case-control study of 384 patients diagnosed with pancreatic cancer from May 2004 to December 2009 and 983 primary care healthy controls in a largely white population (>96%). Our findings showed no significant association between risk of pancreatic cancer and either overall alcohol consumption or type of alcohol consumed (drinks/day). Our study showed dietary folate intake had a modest effect size, but was significantly inversely associated with pancreatic cancer (odds ratio (OR) = 0.99, p < 0.0001). The current study supports the hypothesis that pancreatic cancer risk is reduced with higher food-based folate intake.

Nutrients and the Pancreas: An Epigenetic Perspective.

Pancreatic cancer is the fourth most common cause of cancer-related deaths with a dismal average five-year survival rate of six percent. Substitutional progress has been made in understanding how pancreatic cancer develops and progresses. Evidence is mounting which demonstrates that diet and nutrition are key factors in carcinogenesis. In particular, diets low in folate and high in fruits, vegetables, red/processed meat, and saturated fat have been identified as pancreatic cancer risk factors with a proposed mechanism involving epigenetic modifications or gene regulation. We review the current literature assessing the correlation between diet, epigenetics, and pancreatic cancer.

SIAH and EGFR, Two RAS Pathway Biomarkers, are Highly Prognostic in Locally Advanced and Metastatic Breast Cancer.

BACKGROUND: Metastatic breast cancer exhibits diverse and rapidly evolving intra- and inter-tumor heterogeneity. Patients with similar clinical presentations often display distinct tumor responses to standard of care (SOC) therapies. Genome landscape studies indicate that EGFR/HER2/RAS "pathway" activation is highly prevalent in malignant breast cancers. The identification of therapy-responsive and prognostic biomarkers is paramount important to stratify patients and guide therapies in clinical oncology and personalized medicine. METHODS: In this study, we analyzed matched pairs of tumor specimens collected from 182 patients who received neoadjuvant systemic therapies (NST). Statistical analyses were conducted to determine whether EGFR/HER2/RAS pathway biomarkers and clinicopathological predictors, alone and in combination, are prognostic in breast cancer. FINDINGS: SIAH and EGFR outperform ER, PR, HER2 and Ki67 as two logical, sensitive and prognostic biomarkers in metastatic breast cancer. We found that increased SIAH and EGFR expression correlated with advanced pathological stage and aggressive molecular subtypes. Both SIAH expression post-NST and NST-induced changes in EGFR expression in invasive mammary tumors are associated with tumor regression and increased survival, whereas ER, PR, and HER2 were not. These results suggest that SIAH and EGFR are two prognostic biomarkers in breast cancer with lymph node metastases. INTERPRETATION: The discovery of incorporating tumor heterogeneity-independent and growth-sensitive RAS pathway biomarkers, SIAH and EGFR, whose altered expression can be used to estimate therapeutic efficacy, detect emergence of resistant clones, forecast tumor regression, differentiate among partial responders, and predict patient survival in the neoadjuvant setting, has a clear clinical implication in personalizing breast cancer therapy. FUNDING: This work was supported by the Dorothy G. Hoefer Foundation for Breast Cancer Research (A.H. Tang); Center for Innovative Technology (CIT)-Commonwealth Research Commercialization Fund (CRCF) (MF14S-009-LS to A.H. Tang), and National Cancer Institute (CA140550 to A.H. Tang).