Association of Circulating Tumor DNA Testing Before Tissue Diagnosis With Time to Treatment Among Patients With Suspected Advanced Lung Cancer: The ACCELERATE Nonrandomized Clinical Trial.

Importance: Liquid biopsy has emerged as a complement to tumor tissue profiling for advanced non-small cell lung cancer (NSCLC). The optimal way to integrate liquid biopsy into the diagnostic algorithm for patients with newly diagnosed advanced NSCLC remains unclear. Objective: To evaluate the use of circulating tumor DNA (ctDNA) genotyping before tissue diagnosis among patients with suspected advanced NSCLC and its association with time to treatment. Design, Setting, and Participants: This single-group nonrandomized clinical trial was conducted among 150 patients at the Princess Margaret Cancer Centre-University Health Network (Toronto, Ontario, Canada) between July 1, 2021, and November 30, 2022. Patients referred for investigation and diagnosis of lung cancer were eligible if they had radiologic evidence of advanced lung cancer prior to a tissue diagnosis. Interventions: Patients underwent plasma ctDNA testing with a next-generation sequencing (NGS) assay before lung cancer diagnosis. Diagnostic biopsy and tissue NGS were performed per standard of care. Main Outcome and Measures: The primary end point was time from referral to treatment initiation among patients with advanced nonsquamous NSCLC using ctDNA testing before diagnosis (ACCELERATE [Accelerating Lung Cancer Diagnosis Through Liquid Biopsy] cohort). This cohort was compared with a reference cohort using standard tissue genotyping after tissue diagnosis. Results: Of the 150 patients (median age at diagnosis, 68 years [range, 33-91 years]; 80 men [53%]) enrolled, 90 (60%) had advanced nonsquamous NSCLC. The median time to treatment was 39 days (IQR, 27-52 days) for the ACCELERATE cohort vs 62 days (IQR, 44-82 days) for the reference cohort (P < .001). Among the ACCELERATE cohort, the median turnaround time from sample collection to genotyping results was 7 days (IQR, 6-9 days) for plasma and 23 days (IQR, 18-28 days) for tissue NGS (P < .001). Of the 90 patients with advanced nonsquamous NSCLC, 21 (23%) started targeted therapy before tissue NGS results were available, and 11 (12%) had actionable alterations identified only through plasma testing. Conclusions and Relevance: This nonrandomized clinical trial found that the use of plasma ctDNA genotyping before tissue diagnosis among patients with suspected advanced NSCLC was associated with accelerated time to treatment compared with a reference cohort undergoing standard tissue testing. Trial Registration: ClinicalTrials.gov Identifier: NCT04863924.

Plasma-first: accelerating lung cancer diagnosis and molecular profiling through liquid biopsy.

Introduction: Molecular profiling of tumor tissue is the gold standard for treatment decision-making in advanced non-small cell lung cancer (NSCLC). Results may be delayed or unavailable due to insufficient tissue, prolonged wait times for biopsy, pathology assessment and testing. We piloted the use of plasma testing in the initial diagnostic workup for patients with suspected advanced lung cancer. Methods: Patients with ⩽15 pack-year smoking history and suspected advanced lung cancer referred to the lung cancer rapid diagnostic program underwent plasma circulating-tumor DNA testing using a DNA-based mutation panel. Tissue testing was performed per standard of care, including comprehensive next-generation sequencing (NGS). The primary endpoint was time from diagnostic program referral to cancer treatment in stage IV NSCLC patients (Cohort A) compared to a contemporary cohort not enrolled in the study (Cohort B) and an historical pre-COVID cohort referred to the program between 2018 and 2019 (Cohort C). Results: From January to June 2021, 20 patients were enrolled in Cohort A; median age was 70.5 years (range 33-87), 70% were female, 55% Caucasian, 85% never smokers, and 75% were diagnosed with NSCLC. Seven had actionable alterations detected in plasma or tissue (4/7 concordant). Fusions, not tested in plasma, were identified by immunohistochemistry for three patients. Mean result turnaround time was 17.8 days for plasma NGS and 23.6 days for tissue (p = 0.10). Mean time from referral to treatment initiation was significantly shorter in cohort A at 32.6 days (SD 13.1) versus 62.2 days (SD 31.2) in cohort B and 61.5 days (SD 29.1) in cohort C, both p < 0.0001. Conclusion: Liquid biopsy in the initial diagnostic workup of patients with suspected advanced NSCLC can lead to faster molecular results and shorten time to treatment even with smaller DNA panels. An expansion study using comprehensive NGS plasma testing with faster turnaround time is ongoing (NCT04862924).

The economic value of liquid biopsy for genomic profiling in advanced non-small cell lung cancer.

Background: Liquid biopsy (LB) can detect actionable genomic alterations in plasma circulating tumor circulating tumor DNA beyond tissue testing (TT) alone in advanced non-small cell lung cancer (NSCLC) patients. We estimated the cost-effectiveness of adding LB to TT in the Canadian healthcare system. Methods: A cost-effectiveness analysis was conducted using a decision analytic Markov model from the Canadian public payer (Ontario) perspective and a 2-year time horizon in patients with treatment-naïve stage IV non-squamous NSCLC and ⩽10 pack-year smoking history. LB was performed using the comprehensive genomic profiling Guardant360™ assay. Standard of care TT for each participating institution was performed. Costs and outcomes of molecular testing by LB + TT were compared to TT alone. Transition probabilities were calculated from the VALUE trial (NCT03576937). Sensitivity analyses were undertaken to assess uncertainty in the model. Results: Use of LB + TT identified actionable alterations in more patients, 68.5 versus 52.7% with TT alone. Use of the LB + TT strategy resulted in an incremental cost savings of $3065 CAD per patient (95% CI, 2195-3945) and a gain in quality-adjusted life-years of 0.02 (95% CI, 0.01-0.02) versus TT alone. More patients received chemo-immunotherapy based on TT with higher overall costs, whereas more patients received targeted therapy based on LB + TT with net cost savings. Major drivers of cost-effectiveness were drug acquisition costs and prevalence of actionable alterations. Conclusion: The addition of LB to TT as initial molecular testing of clinically selected patients with advanced NSCLC did not increase system costs and led to more patients receiving appropriate targeted therapy.

Upfront Next Generation Sequencing in Non-Small Cell Lung Cancer.

In advanced non-small cell lung cancer (NSCLC), patients with actionable genomic alterations may derive additional clinical benefit from targeted treatment compared to cytotoxic chemotherapy. Current guidelines recommend extensive testing with next generation sequencing (NGS) panels. We investigated the impact of using a targeted NGS panel (TruSight Tumor 15, Illumina) as reflex testing for NSCLC samples at a single institution. Molecular analysis examined 15 genes for hotspot mutation variants, including AKT1, BRAF, EGFR, ERBB2, FOXL2, GNA11, GNAQ, KIT, KRAS, MET, NRAS, PDGFRA, PIK3CA, RET and TP53 genes. Between February 2017 and October 2020, 1460 samples from 1395 patients were analyzed. 1201 patients (86.1%) had at least one variant identified, most frequently TP53 (47.5%), KRAS (32.2%) or EGFR (24.2%). Among these, 994 patients (71.3%) had clinically relevant variants eligible for treatment with approved therapies or clinical trial enrollment. The incremental cost of NGS beyond single gene testing (EGFR, ALK) was CAD $233 per case. Reflex upfront NGS identified at least one actionable variant in more than 70% of patients with NSCLC, with minimal increase in testing cost. Implementation of NGS panels remains essential as treatment paradigms continue to evolve.

Automating Access to Real-World Evidence.

Introduction: Real-world evidence is important in regulatory and funding decisions. Manual data extraction from electronic health records (EHRs) is time-consuming and challenging to maintain. Automated extraction using natural language processing (NLP) and artificial intelligence may facilitate this process. Whereas NLP offers a faster solution than manual methods of extraction, the validity of extracted data remains in question. The current study compared manual and automated data extraction from the EHR of patients with advanced lung cancer. Methods: Previously, we extracted EHRs from 1209 patients diagnosed with advanced lung cancer (stage IIIB or IV) between January 2015 and December 2017 at Princess Margaret Cancer Centre (Toronto, Canada) using the commercially available artificial intelligence engine, DARWEN (Pentavere, Ontario, Canada). For comparison, 100 of 333 patients that received systemic therapy were randomly selected and clinical data manually extracted by two trained abstractors using the same accepted gold standard feature definitions, including patient, disease characteristics, and treatment data. All cases were re-reviewed by an expert adjudicator. Accuracy and concordance between automated and manual methods are reported. Results: Automated extraction required considerably less time (<1 day) than manual extraction (∼225 person-hr). The collection of demographic data (age, sex, diagnosis) was highly accurate and concordant with both methods (96%-100%). Accuracy (for either extraction approach) and concordance were lower for unstructured data elements in EHR, such as performance status, date of diagnosis, and smoking status (NLP accuracy: 88%-94%; Manual accuracy: 78%-94%; concordance: 71%-82%). Concurrent medications (86%-100%) and comorbid conditions (96%-100%), were reported with high accuracy and concordance. Treatment details were also accurately captured with both methods (84%-100%) and highly concordant (83%-99%). Detection of whether biomarker testing was performed was highly accurate and concordant (96%-98%), although detection of biomarker test results was more variable (accuracy 84%-100%, concordance 84%-99%). Features with syntactic or semantic variation requiring clinical interpretation were extracted with slightly lower accuracy by both NLP and manual review. For example, metastatic sites were more accurately identified through NLP extraction (NLP: 88%-99%; manual: 71%-100%; concordance: 70%-99%) with the exception of lung and lymph node metastases (NLP: 66%-71%; manual: 87%-92%; concordance: 58%) owing to analogous terms used in radiology reports not being included in the accepted gold standard definition. Conclusions: Automated data abstraction from EHR is highly accurate and faster than manual abstraction. Key challenges include poorly structured EHR and the use of analogous terms beyond the accepted gold standard definition. The application of NLP can facilitate real-world evidence studies at a greater scale than could be achieved with manual data extraction.

Integrating comprehensive genomic sequencing of non-small cell lung cancer into a public healthcare system.

OBJECTIVES: Standard molecular testing for patients with stage IV non-small cell lung cancer (NSCLC) in the Canadian publicly funded health system includes single gene testing for EGFR, ALK, and ROS-1. Comprehensive genomic profiling (CGP) may broaden treatment options for patients. This study examined the impact of CGP in a publicly funded health system. METHODS: Consenting patients with stage IV NSCLC without known targetable alterations underwent CGP on diagnostic samples. Patients that had progressed on targeted therapy were also eligible. The CGP assay was a hybrid capture next generation sequencing (NGS) panel (Oncomine Comprehensive Assay Version 3, ThermoFisher). The number of actionable alterations, changes in treatment, clinical trial eligibility and costs as a result of CGP were evaluated and patient willingness-to-pay. RESULTS: Of 182 screened patients,134 (74%) had successful CGP testing. Twenty percent had received prior targeted therapy. Incremental actionable alterations were identified in 31% of patients. The most common novel targets identified were mutations in ERBB2 (exon 20 insertions), MET (exon 14 skipping) and KRAS (G12C). At data cut off (31/12/2020), 16% of patients had a change in treatment as a result of CGP. Additional clinical trial options were identified for 75% of patients. The incremental direct laboratory cost for CGP beyond public reimbursement for single gene tests was $747 CAD/case. CONCLUSION: CGP identifies additional actionable targets beyond single gene tests with a direct impact on patient treatment and increased clinical trial eligibility. These benefits highlight the value of CGP in patients with NSCLC in public health systems.

The financial impact of cancer care on renal cancer patients.

INTRODUCTION Advances in novel treatment options may render renal cell cancer (RCC) patients susceptible to the financial toxicity (FT) of cancer treatment, and the factors associated with FT are unknown. MATERIALS AND METHODS: Eligible patients were ≥ 18 years old and had a diagnosis of stage IV RCC for at least 3 months. Patients were recruited from Princess Margaret Cancer Centre and Sunnybrook Odette Cancer Centre (Toronto, Canada). FT was assessed using the validated Comprehensive Score for Financial Toxicity (COST) instrument, a 12-question survey scored from 0-44, with lower scores reflecting worse FT. Patient and treatment characteristics, out-of-pocket costs (OOP) and private insurance coverage (PIC) were collected. Factors associated with worse FT (COST score < 21) were determined. RESULTS: Sixty-five patients were approached and 80% agreed to participate (n = 52). The median age was 62 (44-88); 20% were female (n = 10); 43% were age ≥ 65 (n = 22); 63% were Caucasian (n = 31). Median COST score was 20.5 (3-44). Factors associated with worse FT were age < 65 (OR 9.5, p = 0.007), high OOP (OR 4.4, p = 0.04) and receiving treatment off clinical trial (in comparison to being on surveillance or on clinical trial) (OR 5.9, p = 0.03), when adjusting for other factors in multivariable logistic regression. However, there was no correlation between annual income or PIC and FT. CONCLUSION: Financial toxicity in the RCC population is more significant in younger patients and those on treatment outside of a clinical trial. Financial aid should be offered to these at-risk patients to optimize adherence to life prolonging RCC treatments.

Reflex ROS1 IHC Screening with FISH Confirmation for Advanced Non-Small Cell Lung Cancer-A Cost-Efficient Strategy in a Public Healthcare System.

ROS1 rearrangements are identified in 1-2% of lung adenocarcinoma cases, and reflex testing is guideline-recommended. We developed a decision model for population-based ROS1 testing from a Canadian public healthcare perspective to determine the strategy that optimized detection of true-positive (TP) cases while minimizing costs and turnaround time (TAT). Eight diagnostic strategies were compared, including reflex single gene testing via immunohistochemistry (IHC) screening, fluorescence in-situ hybridization (FISH), next-generation sequencing (NGS), and biomarker-informed (EGFR/ALK/KRAS wildtype) testing initiated by pathologists and clinician-initiated strategies. Reflex IHC screening with FISH confirmation of positive cases yielded the best results for TAT, TP detection rate, and cost. IHC screening saved CAD 1,000,000 versus reflex FISH testing. NGS was the costliest reflex strategy. Biomarker-informed testing was cost-efficient but delayed TAT. Clinician-initiated testing was the least costly but resulted in long TAT and missed TP cases, highlighting the importance of reflex testing. Thus, reflex IHC screening for ROS1 with FISH confirmation provides a cost-efficient strategy with short TAT and maximizes the number of TP cases detected.

Value assessment of oncology drugs using a weighted criterion-based approach.

BACKGROUND: Globally, the rising cost of anticancer therapy has motivated efforts to quantify the overall value of new cancer treatments. Multicriteria decision analysis offers a novel approach to incorporate multiple criteria and perspectives into value assessment. METHODS: The authors recruited a diverse, multistakeholder group who identified and weighted key criteria to establish the drug assessment framework (DAF). Construct validity assessed the degree to which DAF scores were associated with past pan-Canadian Oncology Drug Review (pCODR) funding recommendations and European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS; version 1.1) scores. RESULTS: The final DAF included 10 criteria: overall survival, progression-free survival, response rate, quality of life, toxicity, unmet need, equity, feasibility, disease severity, and caregiver well-being. The first 5 clinical benefit criteria represent approximately 64% of the total weight. DAF scores ranged from 0 to 300, reflecting both the expected impact of the drug and the quality of supporting evidence. When the DAF was applied to the last 60 drugs (with reviewers blinded) reviewed by pCODR (2015-2018), those drugs with positive pCODR funding recommendations were found to have higher DAF scores compared with drugs not recommended (103 vs 63; Student t test P = .0007). DAF clinical benefit criteria mildly correlated with ESMO-MCBS scores (correlation coefficient, 0.33; 95% CI, 0.009-0.59). Sensitivity analyses that varied the criteria scores did not change the results. CONCLUSIONS: Using a structured and explicit approach, a criterion-based valuation framework was designed to provide a transparent and consistent method with which to value and prioritize cancer drugs to facilitate the delivery of affordable cancer care.

The presence and variant allele fraction of EGFR mutations in ctDNA and development of resistance.

BACKGROUND: Peripheral blood sampling for detection of EGFR T790M in cell-free circulating tumour (ct) DNA in TKI-resistant EGFR mutant (EGFRm) lung cancer is now standard. The value of more comprehensive sequencing is unknown. METHODS: Prospective ctDNA analysis in patients with EGFRm NSCLC was performed using a next generation sequencing (NGS) panel of regions of 11 genes detecting single nucleotide variants and small insertions/deletions at ≥0.1% variant allele frequency (VAF) was performed. Patients were grouped according to treatment phase, including: (A) pre EGFR-TKI, (B) stable or responding to EGFR-TKI, (C) radiographic progression during EGFR-TKI, and (D) during chemotherapy treatment. RESULTS: Seventy-two patients with stage IV EGFRm NSCLC were enrolled and first blood samples were analysed. Primary sensitizing mutations in del19 or L858R were present in 66 (92%) and uncommon EGFRm in 6 (8%). Mutations in ctDNA were found in 53 samples (74%). T790M was detected in 3 of 4 patients with T790M-negative tissue. Other co-occurring EGFRm were found in 10 patients (7%) including K745R during first-line osimertinib. TP53 (n = 10), KRAS (n = 1), PI3KCA (n = 1) and ALK (n = 3) gene mutations also were detected. The presence of an EGFRm (excluding T790M) was associated with untreated or progressive disease, p = 0.04. In TKI-treated patients without radiologic progression, median progression free survival (PFS) was 10 months versus 2.1 months (HR 2.22, 95% CI: 0.89-5.54, p = 0.08) if an EGFRm in ctDNA was detected. If T790M was present in ctDNA, median PFS was 3.0 months versus 9.7 months (HR 4.59, 95% CI: 1.43-14.73, p = 0.005). High % VAF of both EGFRm and T790M correlated with inferior PFS (p = 0.01 and p = 0.03 respectively). CONCLUSION: In addition to the emergence of resistance mutations, the presence of the primary or co-occurring EGFRm in patients receiving EGFR-TKIs may associate with shorter PFS and may be useful in longitudinal analyses of ctDNA to direct therapy.

Financial Burden Among Patients With Lung Cancer in a Publically Funded Health Care System.

INTRODUCTION: Financial distress has been established as a clinically relevant patient-reported outcome associated with worse mortality and quality of life. Our goal was to define factors associated with financial burden (FB) in a public health care system. MATERIALS AND METHODS: Patients with advanced lung cancer were recruited from outpatient clinics at the Princess Margaret Cancer Centre (Toronto, Canada). FB was measured with the validated Comprehensive Score for Financial Toxicity (COST) instrument, a 12-item survey scored from 0 to 44, with lower scores reflecting worse financial well-being. Data on patient and treatment characteristics, total out-of-pocket costs (OOP), and private insurance coverage were collected. Multivariable logistic regression models were fit for COST score and each variable, to determine factors associated with greater FB (COST < 21). RESULTS: Of 251 patients approached, 200 (80%) participated. The median age of the cohort was 65 years; 56% were female. The median total OOP ranged between $1000 and $5000 CAD. The median COST score was 21 (range, 0-44). FB was associated with age, with patients < 65 years reporting greater FB than older patients (COST, 18.0 vs. 24.0; P < .0001). In multivariable logistic regression analysis, younger age was associated with greater FB, when adjusting for income, employment status, OOP, and private insurance coverage (odds ratio, 3.6; 95% confidence interval, 1.5-9.1; P < .0001). CONCLUSION: Age is significantly associated with FB in the Canadian (Ontario) public health care system, with younger patients with lung cancer reporting greater financial distress. This study highlights priority patient populations where FB should be routinely assessed and appropriate resources for support offered.

Evaluation of a validated methylation triage signature for human papillomavirus positive women in the HPV FOCAL cervical cancer screening trial.

Human papillomavirus (HPV)-based cervical cancer screening requires triage of HPV positive women to identify those at risk of cervical intraepithelial neoplasia grade 2 (CIN2) or worse. We conducted a blinded case-control study within the HPV FOCAL randomized cervical cancer screening trial of women aged 25-65 to examine whether baseline methylation testing using the S5 classifier provided triage performance similar to an algorithm relying on cytology and HPV genotyping. Groups were randomly selected from women with known HPV/cytology results and pathology outcomes. Group 1: 104 HPV positive (HPV+), abnormal cytology (54 CIN2/3; 50

Comparative performance of human papillomavirus messenger RNA versus DNA screening tests at baseline and 48 months in the HPV FOCAL trial.

BACKGROUND: HPV FOCAL is a randomized trial comparing high-risk HPV [Hybrid Capture 2 (HC2)] vs. liquid-based cytology (LBC) for primary cervical screening. OBJECTIVE: The present study objective was to compare Aptima HPV (AHPV) and HC2 assay performance at the intervention arm baseline and 48 mo. screens in relation to the rates of cervical intraepithelial neoplasia (CIN) grade 2 or worse (CIN2+). STUDY DESIGN: Women enrolled after December 2010 (n = 3475) were screened at baseline with both AHPV and HC2 (AHPV was blinded). Women with CIN2+ exited the trial; HC2 negative (-) women and those HC2 positive (+) with

Luteolin is a novel p90 ribosomal S6 kinase (RSK) inhibitor that suppresses Notch4 signaling by blocking the activation of Y-box binding protein-1 (YB-1).

Triple-negative breast cancers (TNBC) are notoriously difficult to treat because they lack hormone receptors and have limited targeted therapies. Recently, we demonstrated that p90 ribosomal S6 kinase (RSK) is essential for TNBC growth and survival indicating it as a target for therapeutic development. RSK phosphorylates Y-box binding protein-1 (YB-1), an oncogenic transcription/translation factor, highly expressed in TNBC (~70% of cases) and associated with poor prognosis, drug resistance and tumor initiation. YB-1 regulates the tumor-initiating cell markers, CD44 and CD49f however its role in Notch signaling has not been explored. We sought to identify novel chemical entities with RSK inhibitory activity. The Prestwick Chemical Library of 1120 off-patent drugs was screened for RSK inhibitors using both in vitro kinase assays and molecular docking. The lead candidate, luteolin, inhibited RSK1 and RSK2 kinase activity and suppressed growth in TNBC, including TIC-enriched populations. Combining luteolin with paclitaxel increased cell death and unlike chemotherapy alone, did not enrich for CD44(+) cells. Luteolin's efficacy against drug-resistant cells was further indicated in the primary x43 cell line, where it suppressed monolayer growth and mammosphere formation. We next endeavored to understand how the inhibition of RSK/YB-1 signaling by luteolin elicited an effect on TIC-enriched populations. ChIP-on-ChIP experiments in SUM149 cells revealed a 12-fold enrichment of YB-1 binding to the Notch4 promoter. We chose to pursue this because there are several reports indicating that Notch4 maintains cells in an undifferentiated, TIC state. Herein we report that silencing YB-1 with siRNA decreased Notch4 mRNA. Conversely, transient expression of Flag:YB-1(WT) or the constitutively active mutant Flag:YB-1(D102) increased Notch4 mRNA. The levels of Notch4 transcript and the abundance of the Notch4 intracellular domain (N4ICD) correlated with activation of P-RSK(S221/7) and P-YB-1(S102) in a panel of TNBC cell lines. Silencing YB-1 or RSK reduced Notch4 mRNA and this corresponded with loss of N4ICD. Likewise, the RSK inhibitors, luteolin and BI-D1870, suppressed P-YB-1(S102) and thereby reduced Notch4. In conclusion, inhibiting the RSK/YB-1 pathway with luteolin is a novel approach to blocking Notch4 signaling and as such provides a means of inhibiting TICs.

Small interfering RNA library screen identified polo-like kinase-1 (PLK1) as a potential therapeutic target for breast cancer that uniquely eliminates tumor-initiating cells.

INTRODUCTION: Triple-negative breast cancer (TNBC) high rate of relapse is thought to be due to the presence of tumor-initiating cells (TICs), molecularly defined as being CD44high/CD24-/low. TICs are resilient to chemotherapy and radiation. However, no currently accepted molecular target exists against TNBC and, moreover, TICs. Therefore, we sought the identification of kinase targets that inhibit TNBC growth and eliminate TICs. METHODS: A genome-wide human kinase small interfering RNA (siRNA) library (691 kinases) was screened against the TNBC cell line SUM149 for growth inhibition. Selected siRNAs were then tested on four different breast cancer cell lines to confirm the spectrum of activity. Their effect on the CD44high subpopulation and sorted CD44high/CD24-/low cells of SUM149 also was studied. Further studies were focused on polo-like kinase 1 (PLK1), including its expression in breast cancer cell lines, effect on the CD44high/CD24-/low TIC subpopulation, growth inhibition, mammosphere formation, and apoptosis, as well as the activity of the PLK1 inhibitor, BI 2536. RESULTS: Of the 85 kinases identified in the screen, 28 of them were further silenced by siRNAs on MDA-MB-231 (TNBC), BT474-M1 (ER+/HER2+, a metastatic variant), and HR5 (ER+/HER2+, a trastuzumab-resistant model) cells and showed a broad spectrum of growth inhibition. Importantly, 12 of 28 kinases also reduced the CD44high subpopulation compared with control in SUM149. Further tests of these 12 kinases directly on a sorted CD44high/CD24-/low TIC subpopulation of SUM149 cells confirmed their effect. Blocking PLK1 had the greatest growth inhibition on breast cancer cells and TICs by about 80% to 90% after 72 hours. PLK1 was universally expressed in breast cancer cell lines, representing all of the breast cancer subtypes, and was positively correlated to CD44. The PLK1 inhibitor BI 2536 showed similar effects on growth, mammosphere formation, and apoptosis as did PLK1 siRNAs. Finally, whereas paclitaxel, doxorubicin, and 5-fluorouracil enriched the CD44high/CD24-/low population compared with control in SUM149, subsequent treatment with BI 2536 killed the emergent population, suggesting that it could potentially be used to prevent relapse. CONCLUSION: Inhibiting PLK1 with siRNA or BI 2536 blocked growth of TNBCs including the CD44high/CD24-/low TIC subpopulation and mammosphere formation. Thus, PLK1 could be a potential therapeutic target for the treatment of TNBC as well as other subtypes of breast cancer.

Molecular decoy to the Y-box binding protein-1 suppresses the growth of breast and prostate cancer cells whilst sparing normal cell viability.

The Y-box binding protein-1 (YB-1) is an oncogenic transcription/translation factor that is activated by phosphorylation at S102 whereby it induces the expression of growth promoting genes such as EGFR and HER-2. We recently illustrated by an in vitro kinase assay that a novel peptide to YB-1 was highly phosphorylated by the serine/threonine p90 S6 kinases RSK-1 and RSK-2, and to a lesser degree PKCα and AKT. Herein, we sought to develop this decoy cell permeable peptide (CPP) as a cancer therapeutic. This 9-mer was designed as an interference peptide that would prevent endogenous YB-1(S102) phosphorylation based on molecular docking. In cancer cells, the CPP blocked P-YB-1(S102) and down-regulated both HER-2 and EGFR transcript level and protein expression. Further, the CPP prevented YB-1 from binding to the EGFR promoter in a gel shift assay. Notably, the growth of breast (SUM149, MDA-MB-453, AU565) and prostate (PC3, LNCap) cancer cells was inhibited by ∼90% with the CPP. Further, treatment with this peptide enhanced sensitivity and overcame resistance to trastuzumab in cells expressing amplified HER-2. By contrast, the CPP had no inhibitory effect on the growth of normal immortalized breast epithelial (184htert) cells, primary breast epithelial cells, nor did it inhibit differentiation of hematopoietic progenitors. These data collectively suggest that the CPP is a novel approach to suppressing the growth of cancer cells while sparing normal cells and thereby establishes a proof-of-concept that blocking YB-1 activation is a new course of cancer therapeutics.

Y-box binding protein-1 induces the expression of CD44 and CD49f leading to enhanced self-renewal, mammosphere growth, and drug resistance.

Y-box binding protein-1 (YB-1) is an oncogenic transcription/translation factor expressed in >40% of breast cancers, where it is associated with poor prognosis, disease recurrence, and drug resistance. We questioned whether this may be linked to the ability of YB-1 to induce the expression of genes linked to cancer stem cells such as CD44 and CD49f. Herein, we report that YB-1 binds the CD44 and CD49f promoters to transcriptionally upregulate their expressions. The introduction of wild-type (WT) YB-1 or activated P-YB-1(S102) stimulated the production of CD44 and CD49f in MDA-MB-231 and SUM 149 breast cancer cell lines. YB-1-transfected cells also bound to the CD44 ligand hyaluronan more than the control cells. Similarly, YB-1 was induced in immortalized breast epithelial cells and upregulated CD44. Conversely, silencing YB-1 decreased CD44 expression as well as reporter activity in SUM 149 cells. In mice, expression of YB-1 in the mammary gland induces CD44 and CD49f with associated hyperplasia. Further, activated mutant YB-1(S102D) enhances self-renewal, primary and secondary mammosphere growth, and soft-agar colony growth, which were reversible via loss of CD44 or CD49f. We next addressed the consequence of this system on therapeutic responsiveness. Here, we show that paclitaxel induces P-YB-1(S102) expression, nuclear localization of activated YB-1, and CD44 expression. The overexpression of WT YB-1 promotes mammosphere growth in the presence of paclitaxel. Importantly, targeting YB-1 sensitized the CD44(High)/CD24(Low) cells to paclitaxel. In conclusion, YB-1 promotes cancer cell growth and drug resistance through its induction of CD44 and CD49f.

Phosphorylated insulin-like growth factor-i/insulin receptor is present in all breast cancer subtypes and is related to poor survival.

Drugs that target the insulin-like growth factor-I receptor (IGF-IR) and/or insulin receptor (IR) are currently under investigation for a variety of malignancies including breast cancer. Although we have previously reported that IGF-IR expression in primary breast tumors is common, the activation status of this receptor has not been examined in relation to survival. Phosphorylated IGF-IR/IR (P-IGF-IR/IR) and its downstream signaling partner phospho-S6 (P-S6) were evaluated immunohistochemically in tumor tissue microarrays representing 438 cases of invasive breast cancer. P-IGF-IR/IR (n = 114; P = 0.046) and total levels of IR (n = 122; P = 0.009) were indicative of poor survival, whereas total IGF-IR (n = 112; P = 0.304) was not. P-IGF-IR/IR and P-S6 were coordinately expressed in primary breast tumors (likelihood ratio, 11.57; P = 6.70 x 10(-4)). Importantly, P-IGF-IR/IR was detected in all breast cancer subtypes (luminal, 48.1%; triple negative, 41.9%; and HER2, 64.3%). In vitro, the IGF-IR/IR inhibitor BMS-536924 decreased phospho-RSK and P-S6, and significantly suppressed the growth of breast cancer cell lines MCF-7, SUM149, and AU565 representing the luminal, triple negative, and HER2 subtypes, respectively, in monolayer and soft agar. BMS-536924 also inhibited growth in tamoxifen resistant MCF-7 Tam-R cells while having little effect on immortalized normal breast epithelial cells. Thus, we can determine which patients have the activated receptor and provide evidence that P-IGF-IR/IR is a prognostic factor for breast cancer. Beyond this, P-IGF-IR/IR could be a predictive marker for response to IGF-IR and/or IR-targeted therapies, as these inhibitors may be of benefit in all breast cancer subtypes including those with acquired resistance to tamoxifen.

Redefining prognostic factors for breast cancer: YB-1 is a stronger predictor of relapse and disease-specific survival than estrogen receptor or HER-2 across all tumor subtypes.

INTRODUCTION: Gene expression analysis is used to subtype breast cancers such that the most aggressive tumors are identified, but translating this into clinical practice can be cumbersome. Our goal is to develop a universal biomarker that distinguishes patients at high risk across all breast cancer subtypes. We previously reported that Y-box binding protein-1 (YB-1), a transcription/translation factor, was a marker of poor prognosis in a cohort of 490 patients with breast cancer, but the study was not large enough to subtype the cancers. We therefore investigated whether YB-1 identifies patients at risk for either reduced relapse free survival or decreased r breast cancer specific survival (BCSS) across all tumor subtypes by evaluating 4,049 cases. METHODS: Tumor tissue microarrays, representing 4,049 cases of invasive breast cancers with 20 years of follow up, were subtyped by the expression profiles of estrogen receptor, progesterone receptor, or HER-2. We then addressed whether YB-1 expression identified patients at higher risk for relapse and/or lower BCSS. RESULTS: We found YB-1 to be a highly predictive biomarker of relapse (P < 2.5 x 10(-20)) and poor survival (P < 7.3 x 10(-26)) in the entire cohort and across all breast cancer subtypes. Patients with node-positive or node-negative cancer were more likely to die from the disease if YB-1 was expressed. This was further substantiated using a Cox regression model, which revealed that it was significantly associated with relapse and poor survival in a subtype independent manner (relapse patients, hazard ratio = 1.28, P < 8 x 10(-3); all patients, hazard ratio = 1.45, P < 6.7 x 10(-7)). Moreover, YB-1 was superior to estrogen receptor and HER-2 as a prognostic marker for relapse and survival. For a subset of patients who were originally considered low risk and were therefore not given chemotherapy, YB-1 was indicative of poor survival (P < 7.1 x 10 (-17)). Likewise, YB-1 was predictive of decreased BCSS in tamoxifen-treated patients (P = 0.001); in this setting a Cox regression model once again demonstrated it to be an independent biomarker indicating poor survival (hazard ratio = 1.70, P = 0.022). CONCLUSIONS: Expression of YB-1 universally identifies patients at high risk across all breast cancer subtypes and in situations where more aggressive treatment may be needed. We therefore propose that YB-1 may re-define high-risk breast cancer and thereby create opportunities for individualized therapy.