Abstract PS4-08: Biomarker analysis of paclitaxel, ganitumab, and metformin (PGM) therapy in the I-SPY2 neoadjuvant clinical trial

I-SPY2 is a neoadjuvant trial evaluating experimental therapies in combination with cytotoxic chemotherapy compared to chemotherapy alone with the primary endpoint of pathologic complete response (pCR). Abundant preclinical evidence suggested the type I insulin-like growth factor receptor (IGF-1R) regulated breast cancer growth, although multiple clinical trials did not show benefit. We were the first to report the results of a monoclonal IGF-1R antibody ganitumab (G) in combination with chemotherapy. PGM followed by doxorubicin/cyclophosphamide (AC) did not result in substantial increases in pCR when compared to P followed by AC. In this report, we examined several potential predictive biomarkers.

IGF-1R inhibitors induce hyperglycemia and we examined hemoglobin A1C (HgbA1c) as a measure of glucose control in patients before and after PGM therapy. 106 patients received PGM and 104 patients had baseline HgbA1c with a median of 5.4%. However, 27% (28/104) had levels greater than 5.7% the upper limit of normal as defined by the NIDDK. 4 of 104 had HgbA1c greater than 6.5%, a level associated with type 2 diabetes. pCR rates are similar between patients with baseline HgbA1c ≤5.7% (21%) vs. >5.7% (25%) (Fisher test p=0.79). 72 of these patients had an additional HgbA1c during the course of PGM therapy. For patients with HgbA1c ≤5.7%, 27% (14/52) had subsequent elevation above 5.7% after PGM. For patients with a baseline HgbA1C >5.7%, all 20 patients continued to have elevated levels through PGM.

We also examined pre-treatment tumor gene expression profiles derived from custom Agilent 44K full-genome microarrays. We studied 11 genes associated with the IGF-1R signaling (IGF1, IGF2, IGF1R, INSR, IGFBP2, IRS1, IRS2, IGFBP3, IGFBP4, IGFBP5, CDH1), the IGFBP5/IGFBP4 ratio, and two IGFR expression signatures (Creighton, et al. J Clin Oncol 26:4078 2008 PMID: 18757322; Mu, et al. Breast Cancer Res Treat 133:321 2012 PMID: 22297468). The 2 signatures evaluated: the IGF1 ligand score and the IGF1-R signature are anti-correlated (Rp= - 0.79). In the population as a whole, lower levels of IRS1 and IGFBP5 significantly associated with response to PGM (likelihood ratio test (LR) p< 0.05), as do lower levels of the IGF1 ligand score and higher levels of the IGF-1R signature. However, levels of IRS1 and the two expression signatures also trend toward or are significantly associated with response in the control arm; and treatment interactions for all four biomarkers are non-significant (LR p>0.05). Therefore, none of these biomarkers qualify as specific predictors of response to PGM. Similarly, high MammaPrint scores (MP2) were associated with higher pCR scores in both PGM and Control arms. Previous gene expression profiles were divided into tertiles (low, intermediate, high). Similar to the continuous case, IGF1Rsig-class associates with pCR in both the PGM and control arms (Fisher test p=0.033 and 0.044, respectively), and thus also fails as a specific predictor of response to PGM.

We conclude that PGM therapy results in worsening of glucose control and likely increases serum insulin levels. While IGF gene expression profiling associated with treatment response, they were not specific for PGM. Further, biomarker analysis and strategies to control glucose will be needed to optimize anti-IGF-1R therapies.

Citation Format: Douglas Yee, Paul Haluska, Denise M Wolf, Christina Yau, Amy Wilson, I-SPY2 TRIAL Consortium, Angela DeMichele, Claudine Isaacs, Jane Perlmutter, Joan Venticinque, Hope S Rugo, Richard Schwab, Nola M Hylton, W Fraser Symmans, Michelle E Melisko, Teresa L Helsten, Laura J van't Veer, Donald A Berry, Laura J Esserman. Biomarker analysis of paclitaxel, ganitumab, and metformin (PGM) therapy in the I-SPY2 neoadjuvant clinical trial [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS4-08.

Abstract P6-02-01: The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI

Background: Strong background parenchymal enhancement (BPE) may cause overestimation in tumor volume measured from dynamic contrast-enhanced (DCE) MRI, which may adversely affect the ability of MR tumor volume to predict treatment outcome for patients undergoing neoadjuvant chemotherapy (NAC). Specifically, an overestimation of tumor volume can result in misclassification of patients with complete pathologic response (pCR) as non-responders, leading to less confidence in MRI prediction. As well, overestimation of extent of disease might lead to more aggressive surgical therapy than necessary. This study investigated whether high BPE in the contralateral breast influences the predictive performance of MRI-measured functional tumor volume (FTV) for patients with locally advanced breast cancer undergoing NAC.

Methods: patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Each patient had 4 MRI exams: pre-NAC (T0), after 3 weeks of NAC (T1), between NAC regimens (T2), and post-NAC (T3). FTV was calculated at each MRI exam by summing voxels meeting enhancement thresholds. Background parenchymal enhancement (BPE) in the contralateral breast was calculated automatically as mean percentage enhancement on the early (nominal 150sec post-contrast) image in the fibroglandular tissue segmented from 5 continuous axial slices centered in the inferior-to-superior stack. For each treatment time point, patients having both FTV and BPE measurements were included in the analysis. The area under the ROC curve (AUC) was estimated as the association between FTV and pCR at T1, T2, and T3. The analysis was conducted in the full patient cohort and in sub-cohorts defined by hormone receptor (HR) and HER2 status. In each patient cohort, a cut-off BPE value was selected to classify patients with high vs. low BPE by testing AUCs estimated with low-BPE patients reached maximum when the cut-off value varied from median to maximum in steps of 10%.

Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Table 1 shows the number of patients, pCR rate, and AUC of FTV for predicting pCR using all patients available vs. a subset patients with low BPE (< BPE cut-off). In the full cohort, AUC increased slightly across all time points after patients with high BPE were removed. In the HR+/HER2- subtype, AUC increased at T1 after removal of cases with high BPE (0.65 vs. 0.71). For HR-/HER2+, AUC increased substantially after removal of high BPE cases (0.65 to 0.86 at T1, 0.71 to 0.87 at T2, and 0.71 to 0.89 at T3), with greater improvement at the early time point (T1) compared to later time points (T2 and T3). Only a slight improvement in the AUC was observed in the HR+/HER2+ and HR-/HER2- subtypes across all time points.

Conclusions: High background parenchymal enhancement adversely affected the predictive performance of functional tumor volume measured by DCE-MRI, at early treatment time point for HR+/HER2- and across all time points for HR-/HER2+ cancer subtype. The adverse effect might be offset using subtype-optimized enhancement threshold in calculating functional tumor volume.

Table 1 Effect of BPE on the prediction of pCR using FTV at various treatment time pointsT1T2T3npCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offnpCR rateAUCBPE cut-offFullAll64734%0.662762334%0.701761134%0.6925Subset45334%0.6831133%0.7230534%0.72HR+/HER2-All26218%0.651924918%0.718225518%0.7519Subset13118%0.7124818%0.7120419%0.76HR+/HER2+All10636%0.642110538%0.62269634%0.7120Subset5332%0.668438%0.665740%0.73HR-/HER2+All5175%0.65204774%0.71204973%0.7116Subset3073%0.862871%0.872475%0.89HR-/HER2-All22842%0.682822243%0.751821143%0.6916Subset15940%0.7111137%0.7810540%0.75

Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Roy Harnish, Ella F Jones, Lisa J Wilmes, Jessica Gibbs, Elissa Price, Bonnie N Joe, A. Jo Chien, Donald A Berry, Judy C Boughey, Kathy S Albain, Amy S Clark, Kirsten K Edmiston, Anthony D Elias, Erin D Ellis, David M Euhus, Heather S Han, Claudine Isaacs, Qamar J Khan, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Christina Yau, Smita M Asare, Angela DeMichele, Sally Goudreau, Hiroyuki Abe, Deepa Sheth, Dulcy Wolverton, Kelly Fountain, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Theresa Kuritza, Kevin Morley, Michael Nelson, An Church, Bethany Niell, Jennifer Drukteinis, Karen Y Oh, Neda Jafarian, Kathy Brandt, Sadia Choudhery, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Mohammad Eghedari, Pulin Sheth, Linda Hovanessian-Larsen, Mark Rosen, Elizabeth S McDonald, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Laura J Esserman, Nola M Hylton. The effect of background parenchymal enhancement on the predictive performance of functional tumor volume measured in MRI [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-02-01.

Abstract P3-11-02: Evaluation of patritumab/paclitaxel/trastuzumab over standard paclitaxel/trastuzumab in early stage, high-risk HER2 positive breast cancer: Results from the neoadjuvant I-SPY 2 trial

Background: I-SPY2 is a multicenter, phase 2 trial using response-adaptive randomization within biomarker subtypes to evaluate novel agents as neoadjuvant therapy for high-risk breast cancer. The primary endpoint is pathologic complete response (pCR) at surgery. The goal is to identify (graduate) regimens with ≥ 85% Bayesian predictive probability of success (i.e., demonstrating superiority to control) in a future 300-patient phase 3 1:1 randomized neoadjuvant trial with pCR endpoint within signatures defined by hormone-receptor (HR), HER2, and MammaPrint (MP) status. Regimens may leave the trial for futility (< 10% probability of success), maximum sample size accrual (with probability of success ≥ 10% and < 85%), or safety concerns as recommended by the independent DSMB. For HER2+ patients, the I-SPY2 control arm was 12 weekly cycles of paclitaxel+trastuzumab (TH, control) followed by doxorubicin/cyclophosphamide (AC) q2-3 weeks x4 and surgery. Patritumab is a fully human monoclonal antibody that inhibits HER3. In this experimental arm for HER2+ patients, patritumab was given q3w x 4 cycles (18mg/kg loading dose followed by 9mg/kg/dose) concurrent with paclitaxel and trastuzumab q1w x 12 weeks (PTH, treatment), followed by AC q2-3w.

Methods: Women with tumors ≥ 2.5cm were eligible for screening. MP low/HR+ tumors were ineligible. MRI scans (baseline, 3 weeks after start of therapy, prior to AC, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients. Analysis was intention to treat. Patients who switched to non-protocol therapy count as non-pCR. Patients on treatment arm therapy at the time of arm closure are non-evaluable. Graduation potential was in 3 of 10 pre-defined signatures: all HER2+, HR-/HER2+, and HR+/HER2+.

Results: The PTH regimen was stopped at the recommendation of the Safety Working Group and DSMB based on a safety event (bilateral sensorineural hearing loss, Gr 3) observed in one patient. At the time of arm closure, N=31 patients had received PTH treatment; 4 patients receiving PTH were changed to non-protocol therapy and removed from the analysis. The final estimated pCR report will consider 27 PTH and 31 TH as evaluable patients. Accrual was insufficient to assess graduation, however, there appears to be good signal in the HER2+HR- but not HER2+HR+ signatures.

I-SPY 2 TRIAL Est. pCR at time of arm closureSignaturesPTH (Treatment)N= 31TH (Control)N = 31All (HER2+)0.40 (0.22 - 0.59), n=310.23 (0.09 - 0.37), n=31HR-/HER2+0.64 (0.36 - 0.91), n=110.30 (0.12 - 0.47), n=12HR+/HER2+0.28 (0.08 - 0.48), n=200.20 (0.06 - 0.34), n=19

HR+/HER2+0.28 (0.08 - 0.48), n=200.20 (0.06 - 0.34), n=19The patient who developed Gr3 sensorineural hearing loss 6 days after the 2nd patritumab (and 4th paclitaxel/trastuzumab) treatment, did not recover her hearing after patritumab was stopped, and also reported Gr3 vulvovaginal pain, vulvitis, and vaginal inflammation. Other gynecological symptoms in the PTH arm include: 1 pt with Gr1 vaginal hemorrhage, and 1 pt with Gr2 dyspareunia. There was a higher frequency of Gr3 hypokalaemia (12.5% vs. 3.2%). One pt in the PTH arm reported Gr3 small intestinal obstruction which resolved with conservative management.

Conclusion: The I-SPY 2 study aims to assess the probability that investigational regimens will be successful in a phase 3 neoadjuvant trial; PTH was stopped due to safety concerns, although there was activity in the HER2+ HR- signature. This is the first report of Gr3 hearing loss associated with patritumab/paclitaxel/trastuzumab, and thus attribution is uncertain.

Citation Format: Teresa L Helsten, Shelly S Lo, Christina Yau, Kevin Kalinsky, Anthony D Elias, Anne M Wallace, A. Jo Chien, Janice Lu, Julie E Lang, Kathy S Albain, Erica Stringer-Reasor, Amy S Clark, Judy C Boughey, Erin D Ellis, Douglas Yee, Angela DeMichele, Claudine Isaacs, Jane Perlmutter, Hope S Rugo, Richard Schwab, Nola M. Hylton, W. Fraser Symmans, Michelle E Melisko, Laura J van't Veer, Amy Wilson, Ruby Singhrao, Smita M Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of patritumab/paclitaxel/trastuzumab over standard paclitaxel/trastuzumab in early stage, high-risk HER2 positive breast cancer: Results from the neoadjuvant I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-11-02.

Abstract P3-09-02: Evaluation of a novel agent plus standard neoadjuvant therapy in early stage, high-risk HER2 negative breast cancer: Results from the I-SPY 2 TRIAL

Background: I-SPY2 is a multicenter, response-adaptive randomization phase 2 trial to evaluate novel agents when added to standard neoadjuvant therapy for women with high-risk stage II/III breast cancer - weekly paclitaxel + investigational treatment x 12 wks followed by doxorubicin & cyclophosphamide(AC) q3 wks x 4 vs. weekly paclitaxel/AC (control). The primary endpoint is pathologic complete response (pCR). The goal for all investigational arms is to identify/graduate regimens with ≥85% Bayesian predictive probability of success (i.e. demonstrating superiority to control) in a future 300-patient phase 3 1:1 randomized neoadjuvant trial with a pCR endpoint within signatures defined by hormone-receptor (HR) & HER2 status & MammaPrint (MP). Findings from the graduated, previously reported Pembro4 arm (Nanda et al, ASCO 2017) supported investigation of de-escalating therapy, and determining if pembrolizumab (an anti-PD-1 antibody) alone q3 wks x 4 after weekly paclitaxel x 12 wks + pembrolizumab q3 wks x 4 was sufficient to sustain response without AC.

Methods: Women with tumors ≥2.5cm were eligible for screening. MP low/HR+ were ineligible. MRI scans (at baseline, 3 wks, 12 wks, and prior to surgery) were used in a longitudinal statistical model to predict pCR for individual patients (pts). Pts who receive non-protocol therapy (e.g., carboplatin or AC for the Pembro8-noAC arm) count as non-pCR. Pembro8-noAC was open to HER2- pts for evaluation in 3 of 10 pre-defined signatures: HER2-, HR+/HER2-, and HR-/HER2-. Regimens exit the trial for futility (<10% probability of success), maximum sample size accrual (10% <probability of success <85%), or safety as recommended by the independent DSMB.

Results: Pembro8-noAC was randomized to 73 pts, 3 of whom progressed while receiving pembrolizumab alone on study. Randomization to this arm continued after the first report because the rate of progression during AC over the course of the trial was estimated to be 6.5% based on serial MRI studies. However, notification of the third case prompted the study team to ask the DSMB for the summary response for this arm. Although it did not meet formal stopping rules for either graduation or futility, Pembro8-noAC was not near the target threshold pCR rates of 60% for HR-/HER2- and 30% for HR+/HER2+. As a result of this information, combined with the on-treatment progressions, assignment to Pembro8-noAC was discontinued. Treatment with pembrolizumab alone was no longer allowed due to the potential concern for progression, and investigators were given the option to administer AC with pembrolizumab or proceed with definitive surgery following the 12 weeks of paclitaxel + pembrolizumab. 34 pts had surgery results at the time the study was closed. Of the remaining 39 pts, 34 pts have on-therapy MRI assessments. Estimated pCR rates were based on all pts with information at the time (see table). Immune-related adverse events included grade 3 colitis (n=2), grade 3 pneumonitis (n=1), grade 3 transaminitis (n=1), grade 3 hypothyroidism (n=1), and grade 1-2 adrenal insufficiency (n=5).

Conclusion: Although Pembro8-noAC is performing at least as well as standard paclitaxel/AC, the likelihood is very low that the regimen would be successful in a phase 3 trial. Pembrolizumab alone following 12 weeks of paclitaxel + pembrolizumab was not sufficient to sustain a response. This was quickly assessed with a small number of patients.

Estimated pCR rateSignature(95% prob interval)Pembro8-noACControlHER2-0.210.2(0.09-0.32)(0.15-0.25)HR-/HER2-0.270.27(0.09-0.45)(0.19-0.35)HR+/HER2-0.150.15(0.01-0.29)(0.09-0.20)

Citation Format: Minetta C. Liu, Patricia A Robinson, Christina Yau, Anne M Wallace, A. Jo Chien, Erica Stringer-Reasor, Rita Nanda, Douglas Yee, Kathy S Albain, Judy C Boughey, Heather S Han, Anthony D Elias, Kevin Kalinsky, Amy S Clark, Kathleen Kemmer, Claudine Isaacs, Julie E Lang, Janice Lu, Tara Sanft, Angela DeMichele, Nola M Hylton, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Patricia K Haugen, Amy Wilson, Ruby Singhrao, Smita Asare, Ashish Sanil, Donald A Berry, Laura J Esserman. Evaluation of a novel agent plus standard neoadjuvant therapy in early stage, high-risk HER2 negative breast cancer: Results from the I-SPY 2 TRIAL [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P3-09-02.

Abstract P6-10-02: Assessing biomarkers to inform treatment de-escalation: Mid-treatment biopsy cellularity predicts pCR in the I-SPY 2 Trial

Background: The I-SPY 2 TRIAL enrolls women with locally advanced, molecular high-risk breast cancer. An integrated Residual Cancer Burden (iRCB), based on MRI volume change through treatment, is used to predict pathologic complete response (pCR) in the randomization/evaluation Bayesian engine. With the goal of effective de-escalation of treatment for patients exhibiting an early response, biomarkers are being assessed for their ability to predict pCR, alone or with MR data, during treatment. Here, we present the results of a pilot study to examine if invasive tumor cellularity in mid-treatment tissue core biopsies predicts pCR in a 40-patient cohort of I-SPY 2 patients. Other pathologic variables evaluated include Ki67, tumoral histologic features, and stromal tumor-infiltrating lymphocytes (sTILs).

Methods: I-SPY 2 TRIAL pathologists (N=4) were provided images of H&E-stained and Ki67 IHC- labelled (DAKO/Agilent, clone MIB-1) core biopsy sections from 40 patients at the inter-regimen time point, ~12-weeks into treatment. Of the 40 patients, 35 had 4 cores, 3 had 3 cores, and 2 had 2 cores assessed. In total, images from 153 cores were evaluated. For each core, pathologists were asked to score the % area occupied by tumor bed (treatment changes and/or residual cancer), % of viable invasive tumor (0-100%) within tumor bed (with Nottingham grading, % Ki67 labelled, and % sTILs, using standardized guidelines). As decided by the pathologist group, only cores with identified tumor bed were included in the initial analysis. Concordance between pathologists was assessed for all scored criteria, using % agreement for dichotomous variables, and Pearson correlation (r)/standard deviation (sd) for continuous variables. The maximum and average cellularity recorded over all cores/patient, averaged over all pathologists, were analyzed for association with pCR using t- tests (significance threshold: p<0.05). Fisher’s Exact test was used for dichotomous variables, and Pearson’s correlation for association of continuous variables with the residual cancer burden (RCB) index.

Results: Pathologist were in general agreement about the presence or absence of tumor bed, with greater than 82% agreement between any two (83-96%), and an overall agreement of 77%. For scoring the % of the tumor bed involved by invasive cancer, correlations between pairs of pathologists ranged from 0.79-0.95 (mean(r)=0.87, sd=5%), and agreement on a binary presence/absence of invasive cancer was 78%. Both the mean (t-test: p=7.59E-05) and maximum (t-test: p=0.0012) %invasive tumor at 12 weeks, scored as an average over all pathologists, were significantly higher in patients who did not achieve pCR than in responders. We also treated %invasive cellularity as a dichotomous variable (present/absent). 90% (9/10) of patients scored by all pathologists as 0% invasive tumor cells (absent) achieved a pCR, vs only 20% (6/30) of patients scored as >0% invasive cellularity by one or more pathologists (present) (OR=32, Fisher p=0.0005); yielding a positive predictive value for pCR of 0.9. Ki67 and sTILS at 12 weeks were fairly concordant across pathologists ((r,sd)=(0.92, 8.45%) and (0.82,5.5%), respectively), but did not associate with response (p>0.05 for pCR, RCB01, or RCB index). Tumor histologic grade at 12 weeks, assessed in 29/30 patients with non-zero cellularity, trended toward association (Fisher p=0.078): 44% (4/9) with Grade 3 went on to have a pCR, vs. 15% (2/13) with Grade 2 and 0 with Grade 1. These data demonstrate the utility of invasive tumor cellularity as a predictor of pCR in a clinical setting.

Conclusion: In this pilot study we demonstrate that the absence of invasive cancer cells within identified tumor bed in mid-treatment core biopsy samples is highly predictive of pCR.

Citation Format: Sara J Venters, Denise M Wolf, Lamorna Brown-Swigart, Christina Yau, Amy L Delson, Bev Parker, Ron Balassanian, Jodi Carter, Yunn-Yi Chen, Kimberly Cole, Laila Khazai, Molly Klein, Dina Kokh, Gregor Krings, Sunati Sahoo, Jane Wei, I-SPY 2 TRIAL Consortium, Laura J Esserman, Laura J van't Veer, W Fraser Symmans. Assessing biomarkers to inform treatment de-escalation: Mid-treatment biopsy cellularity predicts pCR in the I-SPY 2 Trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-10-02.

Abstract PD9-04: Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial

Background: In an adaptive randomized trial, when new treatment combinations are being tested, it is important to be able to identify patients who are progressing on treatment so that they can be changed to a different therapeutic regimen. We know that even within the molecularly high risk patients in I-SPY 2, there is considerable variation in biology. In this study, we will present results of using MRI-calculated functional tumor volume (FTV) to identify tumor progression for each breast cancer subtype.

Methods: Patients (n=990) enrolled in the I-SPY 2 TRIAL who were randomized to the graduated experimental drug arms or controls from 2010 to 2016 were analyzed. Four MRI exams were performed for each patient: pre-NAC (T0), after 3 weeks of NAC (T1), between regimens (T2), and post-NAC (T3). Functional tumor volume (FTV) was calculated at each exam by summing voxels meeting enhancement thresholds. Tumor progression at T1, T2 or T3 was identified by a positive FTV change relative to T0. Visual inspection was used to exclude false progression due to strong background parenchymal enhancement post-contrast, prominent vessels, motion, or insufficient image quality. pCR was defined as no invasive disease in the breast and lymph nodes. Negative predictive value for pCR was defined as:NPV=number of true non-pCRs / number of patients with MRI assessed tumor progressions, where “true non-pCRs” referred to patients who were non-pCRs at surgery and were assessed as progressors by MRI. The analysis was performed in the full cohort and in sub-cohorts defined by HR and HER2 statuses.

Results: Out of 990 patients, 878 had pCR outcome data (pCR or non-pCR, pCR rate = 35%). Total and non-pCR numbers for each subtype, number of patients with tumor progression assessed by MRI at T1, T2, and T3, and NPVs, are shown in Table 1. In the full cohort, the NPV increased consistently over treatment, from T1 (NPV=83%) to T2 (93%), and to T3 (100%). The HER2+ cancer subtypes showed fewer MRI-assessed tumor progressions than HER2- subtypes: e.g. 10/209 (5%) vs. 108/669 (16%) at T1. NPV was 100% for HER2+ subtypes at T1 and T2 except for a single misclassification of a HR- tumor at T1. Only 6 tumor progressors, all HER2- were identified at T3, and all were confirmed at surgery as non-pCRs (NPV=100%). For HR+/HER2-, the NPV increased slightly from 89% at T1 to 91% at T2, while triple negative subtype had a more substantial increase, from 78% to 92%.

Conclusions: Our study showed strong association between tumor progressors assessed by MRI with true non-pCRs after NAC. For HER2+ tumors, although MRI progressors are rare, they strongly indicate non-pCR at all treatment time points, while HER2- subtypes show more accurate results later in treatment. We are evaluating MRI change at 6 weeks to determine if that time point is sufficient to predict progressors.

Table 1 MRI assessed tumor progression at different treatment time pointN/non-pCRs/%non-pCRMRI assessed tumor progressionT1 (after 3 weeks)T2 (inter-regimen)T3 (post-NAC)NNPV (%)NNPV (%)NNPV (%)Full cohort878/572/65%11883.14192.76100%HR+/HER2-344/280/81%4588.91190.93100%HR+/HER2+134/85/63%610021000N/AHR-/HER2+75/23/31%47521000N/Atriple negative325/184/57%6377.82692.33100%

Citation Format: Wen Li, Natsuko Onishi, David C Newitt, Jessica Gibbs, Lisa J Wilmes, Ella F Jones, Bonnie N Joe, Laura S Sit, Christina Yau, A. Jo Chien, Elissa Price, Kathy S Albain, Theresa Kuritza, Kevin Morley, Judy C Boughey, Kathy Brandt, Sadia Choudhery, Amy S Clark, Mark Rosen, Elizabeth S McDonald, Anthony D Elias, Dulcy Wolverton, Kelly Fountain, David M Euhus, Heather S Han, Bethany Niell, Jennifer Drukteinis, Julie E Lang, Janice Lu, Jane L Meisel, Zaha Mitri, Rita Nanda, Donald W Northfelt, Tara Sanft, Erica Stringer-Reasor, Rebecca K Viscusi, Anne M Wallace, Douglas Yee, Rachel Yung, Smita M Asare, Michelle E Melisko, Jane Perlmutter, Hope S Rugo, Richard Schwab, W. Fraser Symmans, Laura J van't Veer, Donald A Berry, Angela DeMichele, Hiroyuki Abe, Deepa Sheth, Kirsten K Edmiston, Erin D Ellis, Richard Ha, Ralph Wynn, Erin P Crane, Charlotte Dillis, Michael Nelson, An Church, Claudine Isaacs, Qamar J Khan, Karen Y Oh, Neda Jafarian, Dae Hee Bang, Christiane Mullins, Stefanie Woodard, Kathryn W Zamora, Haydee Ojeda-Fornier, Pulin Sheth, Linda Hovanessian-Larsen, Mohammad Eghtedari, Michael Spektor, Marina Giurescu, Mary S Newell, Michael A Cohen, Elise Berman, Constance Lehman, William Smith, Kim Fitzpatrick, Marisa H Borders, Wei Yang, Basak Dogan, Sally Goudreau, Thelma Brown, Laura J Esserman, Nola M Hylton. Breast cancer subtype specific association of pCR with MRI assessed tumor volume progression during NAC in the I-SPY 2 trial [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr PD9-04.

Abstract LB-102: Landscape analysis of the initial data release from AACR Project GENIE

AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) is a multi-phase, multi-year, international data-sharing consortium whose goal is to generate an evidence base for precision cancer medicine by integrating and linking clinical-grade cancer genomic data with clinical outcome data for tens of thousands of cancer patients treated at multiple institutions worldwide. The project fulfills an unmet need in oncology by providing the statistical power necessary to identify novel therapeutic targets, to understand genomic determinants of response to therapy, to design new biomarker-driven clinical trials and ultimately, to improve clinical decision-making and the care delivered to patients. Here we describe the goals, structure and data standards of the GENIE consortium and conclusions from a high-level analysis of the first public release of genomic and limited clinical data from approximately 19,000 patients treated at eight cancer centers obtained during this initial phase of the project. We also explore the clinical utility of these genomic data by examining rates of clinical actionability across multiple cancer types and by estimating patient enrollment rates to the NCI MATCH Trial. Based on yearly rates of sequencing at each of the eight founding institutions, together with the planned addition of new members, we estimate the GENIE database could grow to >100,000 samples within five years. Consistent with the goals of the proposed Cancer Moonshot National Cancer Data Ecosystem, GENIE is committed to the principles of generating interoperable, open access data that can be widely shared across the entire scientific community.

Citation Format: Ethan Cerami, Alexander S. Baras, Justin Guinney, Eva Lepisto, Trevor J. Pugh, Nikolaus Schultz, Thomas Stricker, Shawn M. Sweeney, Laura J. van't Veer, Gerrit A. Meijer, Fabrice Andre, Victor E. Velculescu, Kenna R. Shaw, Mia A. Levy, Philippe L. Bedard, Barrett J. Rollins, Charles L. Sawyers, on behalf of the AACR Project GENIE Consortium. Landscape analysis of the initial data release from AACR Project GENIE [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-102. doi:10.1158/1538-7445.AM2017-LB-102

70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer

BACKGROUND

The 70-gene signature test (MammaPrint) has been shown to improve prediction of clinical outcome in women with early-stage breast cancer. We sought to provide prospective evidence of the clinical utility of the addition of the 70-gene signature to standard clinical-pathological criteria in selecting patients for adjuvant chemotherapy.

METHODS

In this randomized, phase 3 study, we enrolled 6693 women with early-stage breast cancer and determined their genomic risk (using the 70-gene signature) and their clinical risk (using a modified version of Adjuvant! Online). Women at low clinical and genomic risk did not receive chemotherapy, whereas those at high clinical and genomic risk did receive such therapy. In patients with discordant risk results, either the genomic risk or the clinical risk was used to determine the use of chemotherapy. The primary goal was to assess whether, among patients with high-risk clinical features and a low-risk gene-expression profile who did not receive chemotherapy, the lower boundary of the 95% confidence interval for the rate of 5-year survival without distant metastasis would be 92% (i.e., the noninferiority boundary) or higher.

RESULTS

A total of 1550 patients (23.2%) were deemed to be at high clinical risk and low genomic risk. At 5 years, the rate of survival without distant metastasis in this group was 94.7% (95% confidence interval, 92.5 to 96.2) among those not receiving chemotherapy. The absolute difference in this survival rate between these patients and those who received chemotherapy was 1.5 percentage points, with the rate being lower without chemotherapy. Similar rates of survival without distant metastasis were reported in the subgroup of patients who had estrogen-receptor-positive, human epidermal growth factor receptor 2-negative, and either node-negative or node-positive disease.

CONCLUSIONS

Among women with early-stage breast cancer who were at high clinical risk and low genomic risk for recurrence, the receipt of no chemotherapy on the basis of the 70-gene signature led to a 5-year rate of survival without distant metastasis that was 1.5 percentage points lower than the rate with chemotherapy. Given these findings, approximately 46% of women with breast cancer who are at high clinical risk might not require chemotherapy. (Funded by the European Commission Sixth Framework Program and others; ClinicalTrials.gov number, NCT00433589; EudraCT number, 2005-002625-31.).

Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

Mitochondrial genomes are separated from the nuclear genome for most of the cell cycle by the nuclear double membrane, intervening cytoplasm, and the mitochondrial double membrane. Despite these physical barriers, we show that somatically acquired mitochondrial-nuclear genome fusion sequences are present in cancer cells. Most occur in conjunction with intranuclear genomic rearrangements, and the features of the fusion fragments indicate that nonhomologous end joining and/or replication-dependent DNA double-strand break repair are the dominant mechanisms involved. Remarkably, mitochondrial-nuclear genome fusions occur at a similar rate per base pair of DNA as interchromosomal nuclear rearrangements, indicating the presence of a high frequency of contact between mitochondrial and nuclear DNA in some somatic cells. Transmission of mitochondrial DNA to the nuclear genome occurs in neoplastically transformed cells, but we do not exclude the possibility that some mitochondrial-nuclear DNA fusions observed in cancer occurred years earlier in normal somatic cells.

The Neoadjuvant Model Is Still the Future for Drug Development in Breast Cancer

The many improvements in breast cancer therapy in recent years have so lowered rates of recurrence that it is now difficult or impossible to conduct adequately powered adjuvant clinical trials. Given the many new drugs and potential synergistic combinations, the neoadjuvant approach has been used to test benefit of drug combinations in clinical trials of primary breast cancer. A recent FDA-led meta-analysis showed that pathologic complete response (pCR) predicts disease-free survival (DFS) within patients who have specific breast cancer subtypes. This meta-analysis motivated the FDA's draft guidance for using pCR as a surrogate endpoint in accelerated drug approval. Using pCR as a registration endpoint was challenged at ASCO 2014 Annual Meeting with the presentation of ALTTO, an adjuvant trial in HER2-positive breast cancer that showed a nonsignificant reduction in DFS hazard rate for adding lapatinib, a HER-family tyrosine kinase inhibitor, to trastuzumab and chemotherapy. This conclusion seemed to be inconsistent with the results of NeoALTTO, a neoadjuvant trial that found a statistical improvement in pCR rate for the identical lapatinib-containing regimen. We address differences in the two trials that may account for discordant conclusions. However, we use the FDA meta-analysis to show that there is no discordance at all between the observed pCR difference in NeoALTTO and the observed HR in ALTTO. This underscores the importance of appropriately modeling the two endpoints when designing clinical trials. The I-SPY 2/3 neoadjuvant trials exemplify this approach.

Imaging features of HER2 overexpression in breast cancer: a systematic review and meta-analysis

Breast cancer imaging phenotype is diverse and may relate to molecular alterations driving cancer behavior. We systematically reviewed and meta-analyzed relations between breast cancer imaging features and human epidermal growth factor receptor type 2 (HER2) overexpression as a marker of breast cancer aggressiveness. MEDLINE and EMBASE were searched for mammography, breast ultrasound, magnetic resonance imaging (MRI), and/or [(18)F]fluorodeoxyglucose positron emission tomography studies through February 2013. Of 68 imaging features that could be pooled (85 articles, 23,255 cancers; random-effects meta-analysis), 11 significantly related to HER2 overexpression. Results based on five or more studies and robustness in subgroup analyses were as follows: the presence of microcalcifications on mammography [pooled odds ratio (pOR), 3.14; 95% confidence interval (CI), 2.46-4.00] or ultrasound (mass-associated pOR, 2.95; 95% CI, 2.34-3.71), branching or fine linear microcalcifications (pOR, 2.11; 95% CI, 1.07-4.14) or extremely dense breasts on mammography (pOR, 1.37; 95% CI, 1.07-1.76), and washout (pOR, 1.57; 95% CI, 1.11-2.21) or fast initial kinetics (pOR, 2.60; 95% CI, 1.43-4.73) on MRI all increased the chance of HER2 overexpression. Maximum [(18)F]fluorodeoxyglucose standardized uptake value (SUVmax) was higher upon HER2 overexpression (pooled mean difference, +0.76; 95% CI, 0.10-1.42). These results show that several imaging features relate to HER2 overexpression, lending credibility to the hypothesis that imaging phenotype reflects cancer behavior. This implies prognostic relevance, which is especially relevant as imaging is readily available during diagnostic work-up.

Breast and ovarian cancer risks in a large series of clinically ascertained families with a high proportion of BRCA1 and BRCA2 Dutch founder mutations

BACKGROUND

BRCA1 or BRCA2 mutations confer increased risks of breast and ovarian cancer, but risks have been found to vary across studies and populations.

METHODS

We ascertained pedigree data of 582 BRCA1 and 176 BRCA2 families and studied the variation in breast and ovarian cancer risks using a modified segregation analysis model.

RESULTS

The average cumulative breast cancer risk by age 70 years was estimated to be 45% (95% CI 36 to 52%) for BRCA1 and 27% (95% CI 14 to 38%) for BRCA2 mutation carriers. The corresponding cumulative risks for ovarian cancer were 31% (95% CI 17 to 43%) for BRCA1 and 6% (95% CI 2 to 11%) for BRCA2 mutation carriers. In BRCA1 families, breast cancer relative risk (RR) increased with more recent birth cohort (p heterogeneity = 0.0006) and stronger family histories of breast cancer (p heterogeneity < 0.001). For BRCA1, our data suggest a significant association between the location of the mutation and the ratio of breast to ovarian cancer (p<0.001). By contrast, in BRCA2 families, no evidence was found for risk heterogeneity by birth cohort, family history or mutation location.

CONCLUSIONS

BRCA1 mutation carriers conferred lower overall breast and ovarian cancer risks than reported so far, while the estimates of BRCA2 mutations were among the lowest. The low estimates for BRCA1 might be due to older birth cohorts, a moderate family history, or founder mutations located within specific regions of the gene. These results are important for a more accurate counselling of BRCA1/2 mutation carriers.

A gene signature for late distant metastasis in breast cancer identifies a potential mechanism of late recurrences

INTRODUCTION

Breast cancer risk of recurrence is known to span 20 years, yet existing prognostic signatures are best at predicting early recurrences (≤ 5 years). There is a critical need to identify those patients at risk of late-relapse (>5 years), in order to select potential candidates for further treatment and to identify molecular targets for such treatment.

METHODS

A total of 252 breast primary tumors were selected at the Netherlands Cancer Institute from a retrospective series of ER+, HER2- breast cancer patients with a follow-up of at least 10 years. Gene expression analysis was performed using Agilent 4x44K microarrays. Patients were classified in 3 groups: no relapse (M0); relapse before 5 years (M0-5) or after 5 years (M5-15). We assessed the correlation of clinico-pathological variables with late Distant Metastases (DM). We divided the patient series into a training set of untreated patients (n = 140) and a test set of treated patients (n = 112), to investigate whether a gene-signature or single genes could be identified for predicting late DM. Pathway level late DM correlates were identified using PARADIGM and DAVID.

RESULTS

Of the clinico-pathologic variables tested, only lymph node status associated with late DM. A 241-gene signature developed on the NKI training set was able to classify M5-15 patients in the test set with a sensitivity of 77% and a specificity of 33% (AUC 0.654). This signature showed enrichment in genes involved in immune response and extracellular matrix. An alternative analysis of individual genes identified CH25H as an independent predictor of distant metastasis in our patient series.

CONCLUSIONS

We identified a gene signature for late metastasis in breast cancer. Our data are consistent with a model in which suppressed anti-tumoral immunity enables dormant tumor cells to re-enter the cell cycle to form metastases in response to extrinsic events in the microenvironment.

Cross-platform pathway-based analysis identifies markers of response to the PARP inhibitor olaparib

Poly(ADP-ribose) polymerase (PARP) is an enzyme involved in DNA repair. PARP inhibitors can act as chemosensitizers, or operate on the principle of synthetic lethality when used as single agent. Clinical trials have shown drugs in this class to be promising for BRCA mutation carriers. We postulated that inability to demonstrate response in non-BRCA carriers in which BRCA is inactivated by other mechanisms or with deficiency in homologous recombination for DNA repair is due to lack of molecular markers that define a responding subpopulation. We identified candidate markers for this purpose for olaparib (AstraZeneca) by measuring inhibitory effects of nine concentrations of olaparib in 22 breast cancer cell lines and identifying features in transcriptional and genome copy number profiles that were significantly correlated with response. We emphasized in this discovery process genes involved in DNA repair. We found that the cell lines that were sensitive to olaparib had a significant lower copy number of BRCA1 compared to the resistant cell lines (p value 0.012). In addition, we discovered seven genes from DNA repair pathways whose transcriptional levels were associated with response. These included five genes (BRCA1, MRE11A, NBS1, TDG, and XPA) whose transcript levels were associated with resistance and two genes (CHEK2 and MK2) whose transcript levels were associated with sensitivity. We developed an algorithm to predict response using the seven-gene transcription levels and applied it to 1,846 invasive breast cancer samples from 8 U133A/plus 2 (Affymetrix) data sets and found that 8–21 % of patients would be predicted to be responsive to olaparib. A similar response frequency was predicted in 536 samples analyzed on an Agilent platform. Importantly, tumors predicted to respond were enriched in basal subtype tumors. Our studies support clinical evaluation of the utility of our seven-gene signature as a predictor of response to olaparib.

An "elite hacker": breast tumors exploit the normal microenvironment program to instruct their progression and biological diversity

The year 2011 marked the 40 year anniversary of Richard Nixon signing the National Cancer Act, thus declaring the beginning of the "War on Cancer" in the United States. Whereas we have made tremendous progress toward understanding the genetics of tumors in the past four decades, and in developing enabling technology to dissect the molecular underpinnings of cancer at unprecedented resolution, it is only recently that the important role of the stromal microenvironment has been studied in detail. Cancer is a tissue-specific disease, and it is becoming clear that much of what we know about breast cancer progression parallels the biology of the normal breast differentiation, of which there is still much to learn. In particular, the normal breast and breast tumors share molecular, cellular, systemic and microenvironmental influences necessary for their progression. It is therefore enticing to consider a tumor to be a "rogue hacker"--one who exploits the weaknesses of a normal program for personal benefit. Understanding normal mammary gland biology and its "security vulnerabilities" may thus leave us better equipped to target breast cancer. In this review, we will provide a brief overview of the heterotypic cellular and molecular interactions within the microenvironment of the developing mammary gland that are necessary for functional differentiation, provide evidence suggesting that similar biology--albeit imbalanced and exaggerated--is observed in breast cancer progression particularly during the transition from carcinoma in situ to invasive disease. Lastly we will present evidence suggesting that the multigene signatures currently used to model cancer heterogeneity and clinical outcome largely reflect signaling from a heterogeneous microenvironment-a recurring theme that could potentially be exploited therapeutically.

The role of genetic breast cancer susceptibility variants as prognostic factors

Recent genome-wide association studies identified 11 single nucleotide polymorphisms (SNPs) associated with breast cancer (BC) risk. We investigated these and 62 other SNPs for their prognostic relevance. Confirmed BC risk SNPs rs17468277 (CASP8), rs1982073 (TGFB1), rs2981582 (FGFR2), rs13281615 (8q24), rs3817198 (LSP1), rs889312 (MAP3K1), rs3803662 (TOX3), rs13387042 (2q35), rs4973768 (SLC4A7), rs6504950 (COX11) and rs10941679 (5p12) were genotyped for 25 853 BC patients with the available follow-up; 62 other SNPs, which have been suggested as BC risk SNPs by a GWAS or as candidate SNPs from individual studies, were genotyped for replication purposes in subsets of these patients. Cox proportional hazard models were used to test the association of these SNPs with overall survival (OS) and BC-specific survival (BCS). For the confirmed loci, we performed an accessory analysis of publicly available gene expression data and the prognosis in a different patient group. One of the 11 SNPs, rs3803662 (TOX3) and none of the 62 candidate/GWAS SNPs were associated with OS and/or BCS at P<0.01. The genotypic-specific survival for rs3803662 suggested a recessive mode of action [hazard ratio (HR) of rare homozygous carriers=1.21; 95% CI: 1.09-1.35, P=0.0002 and HR=1.29; 95% CI: 1.12-1.47, P=0.0003 for OS and BCS, respectively]. This association was seen similarly in all analyzed tumor subgroups defined by nodal status, tumor size, grade and estrogen receptor. Breast tumor expression of these genes was not associated with prognosis. With the exception of rs3803662 (TOX3), there was no evidence that any of the SNPs associated with BC susceptibility were associated with the BC survival. Survival may be influenced by a distinct set of germline variants from those influencing susceptibility.

Abstract 4558: FDG-PET uptake in breast cancer molecular subtypes

Background: Data on breast cancer FDG uptake in relation to clinically relevant molecular subtypes and their interaction is scarce. Some have shown higher standardized uptake values (SUV) in triple negative (TN) and HER2+ than hormone receptor (HR)+ disease. We hypothesize that FDG uptake in HER2+ disease depends on HR status. Methods: We identified 186 invasive breast cancer patients with a whole body FDG-PET/CT scan between 2005 and 2010 at UCSF (within 6 months prior to or after diagnosis but before therapy). Receptor expression was assessed on adjuvant therapy naïve specimens using IHC (HR [ER and PR], HER2) and FISH (HER2) according to clinical practice. We related routinely assessed (log-transformed) SUVmax to receptor expression with linear regression and analysis of covariance (ANCOVA), and adjusted for tumor grade. Results: SUVmax was reported for 160 primary breast cancers and 154 had complete data for HR and HER2. Median age at diagnosis was 52 years (range 21-87), and 34% had localized, 52% regional, and 14% distant disease. Average tumor size was 3.9 cm (SD 2.2), and 12% had good, 51% moderate and 37% poor grade. FDG uptake strongly depended on molecular subtype (Table). Uptake was lowest in HER2-HR+ and somewhat - but not significantly - higher in HER2+HR- disease. The highest SUVmax was found in HER2+HR+, followed by TN disease (both significantly higher than HER2-HR+). The interaction between HR and HER2 in relation to FDG uptake was significant (P=0.003). ANCOVA showed that the higher TN uptake could largely be explained by differences in grade, whereas SUVmax in HER2+HR+ disease remained significantly higher than in HER2-HR+ disease. Conclusion: This large series of advanced primary breast cancer showed FDG uptake to be comparably low in HER2-HR+ and HER2+HR- disease, but significantly higher in HER2+HR+ and TN disease. Tumor grade largely explained the higher FDG uptake in TN disease but not the results for HER2+HR+. FDG-PET may need evaluation at different settings taking into account uptake variation due to tumor biology.

Chemotherapy response and recurrence-free survival in neoadjuvant breast cancer depends on biomarker profiles: results from the I-SPY 1 TRIAL (CALGB 150007/150012; ACRIN 6657)

Neoadjuvant chemotherapy for breast cancer allows individual tumor response to be assessed depending on molecular subtype, and to judge the impact of response to therapy on recurrence-free survival (RFS). The multicenter I-SPY 1 TRIAL evaluated patients with ≥ 3 cm tumors by using early imaging and molecular signatures, with outcomes of pathologic complete response (pCR) and RFS. The current analysis was performed using data from patients who had molecular profiles and did not receive trastuzumab. The various molecular classifiers tested were highly correlated. Categorization of breast cancer by molecular signatures enhanced the ability of pCR to predict improvement in RFS compared to the population as a whole. In multivariate analysis, the molecular signatures that added to the ability of HR and HER2 receptors, clinical stage, and pCR in predicting RFS included 70-gene signature, wound healing signature, p53 mutation signature, and PAM50 risk of recurrence. The low risk signatures were associated with significantly better prognosis, and also identified additional patients with a good prognosis within the no pCR group, primarily in the hormone receptor positive, HER-2 negative subgroup. The I-SPY 1 population is enriched for tumors with a poor prognosis but is still heterogeneous in terms of rates of pCR and RFS. The ability of pCR to predict RFS is better by subset than it is for the whole group. Molecular markers improve prediction of RFS by identifying additional patients with excellent prognosis within the no pCR group.

A prognostic gene expression profile that predicts circulating tumor cell presence in breast cancer patients

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into "good prognosis" or "poor prognosis" are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the "CTC profile" also provided prognostic information independent of the well-established and powerful '70-gene' prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays.

The prognostic significance of tumour cell detection in the peripheral blood versus the bone marrow in 733 early-stage breast cancer patients

Introduction

The detection of circulating tumour cells (CTCs) in the peripheral blood and disseminated tumour cells (DTCs) in the bone marrow are promising prognostic tools for risk stratification in early breast cancer. There is, however, a need for further validation of these techniques in larger patient cohorts with adequate follow-up periods.

Methods

We assayed CTCs and DTCs at primary surgery in 733 stage I or II breast cancer patients with a median follow-up time of 7.6 years. CTCs were detected in samples of peripheral blood mononuclear cells previously stored in liquid-nitrogen using a previously-developed multi-marker quantitative PCR (QPCR)-based assay. DTCs were detected in bone marrow samples by immunocytochemical analysis using anti-cytokeratin antibodies.

Results

CTCs were detected in 7.9% of patients, while DTCs were found in 11.7%. Both CTC and DTC positivity predicted poor metastasis-free survival (MFS) and breast cancer-specific survival (BCSS); MFS hazard ratio (HR) = 2.4 (P < 0.001)/1.9 (P = 0.006), and BCSS HR = 2.5 (P < 0.001)/2.3 (P = 0.01), for CTC/DTC status, respectively). Multivariate analyses demonstrated that CTC status was an independent prognostic variable for both MFS and BCSS. CTC status also identified a subset of patients with significantly poorer outcome among low-risk node negative patients that did not receive adjuvant systemic therapy (MFS HR 2.3 (P = 0.039), BCSS HR 2.9 (P = 0.017)). Using both tests provided increased prognostic information and indicated different relevance within biologically dissimilar breast cancer subtypes.

Conclusions

These results support the use of CTC analysis in early breast cancer to generate clinically useful prognostic information.

A clinicopathologic analysis of peritoneal metastases of colorectal and appendiceal origin

OBJECTIVE

To predict clinical outcome by classification of peritoneal metastases (PM) of colorectal or appendiceal origin.

BACKGROUND

This study investigates whether standardized histological classification can predict outcome for PM of colorectal or appendiceal origin treated with cytoreduction and hyperthermic intraperitoneal chemotherapy (HIPEC).

METHODS

Histology of PM (n = 269) was evaluated by analysis of mitotic activity, atypia, cellularity, and mucinous component. For overall survival (OS) and disease-free survival (DFS) Cox proportional-hazard models were constructed. Covariates included tumor, patient, and treatment characteristics.

RESULTS

PM could be categorized into four groups: low-grade, well-differentiated mucinous tumor (DPAM); intermediated-grade mucinous carcinoma (PMCA-i); high-grade mucinous carcinoma (PMCA); and high-grade nonmucinous carcinoma (PCA). Multivariate analysis showed that histological classification, gender, number of segments affected, completeness of cytoreduction, and HIPEC as primary treatment were significant related to OS and DFS. The 5-year OS was 64% in the DPAM group, 36% in the PMCA group, and 24% in the PCA group. Of PM originating from an appendix tumor, 29% were of non-DPAM type. Of primary colorectal tumors, 37% resulted in mucinous PM, and another 26% of PM of colorectal origin had partly mucinous histology.

CONCLUSION

Histology is a significant predictive factor of OS and DFS in PM treated with surgical cytoreduction and HIPEC. Low-grade PM (DPAM) should be regarded as a separate entity because of its clearly different clinical course. High-grade mucinous PM has significant better prognosis than nonmucinous PM and should thus be distinguished.

Calibration and discriminatory accuracy of prognosis calculation for breast cancer with the online Adjuvant! program: a hospital-based retrospective cohort study

BACKGROUND

Adjuvant! is a web-based program that calculates individualised 10-year survival probabilities and predicted benefit of adjuvant systemic therapy. The Adjuvant! model has not been validated in any large European series. The aim of our study was to validate Adjuvant! in Dutch patients, investigating both its calibration and discriminatory accuracy.

METHODS

Patients who were at least partly treated at the Netherlands Cancer Institute for breast cancer between 1987 and 1998 were included if they met the following criteria: tumour size T1 (< or =2 cm), T2 (2-5 cm), or T3 (>5 cm), invasive breast carcinoma, with information about involvement of axillary lymph nodes available, no distant metastases, primary surgery, axillary staging, and radiotherapy according to national guidelines. Clinicopathological characteristics and adjuvant treatment data were retrieved from hospital records and medical registries and were entered into the Adjuvant! (version 8.0) batch processor with blinding to outcome. Endpoints were overall survival and the proportion of patients that did not die from breast cancer (breast-cancer-specific survival [BCSS]).

FINDINGS

5380 patients were included with median follow-up of 11.7 years (range 0.03-21.8). The 10-year observed overall survival (69.0%) and BCSS (78.6%) and Adjuvant! predicted overall survival (69.1%) and BCSS (77.8%) were not statistically different (p=0.87 and p=0.18, respectively). Moreover, differences between predicted and observed outcomes were within 2% for most relevant clinicopathological subgroups. In patients younger than 40 years, Adjuvant! overestimated overall survival by 4.2% (p=0.04) and BCSS by 4.7% (p=0.01). The concordance index, which indicates discriminatory accuracy at the individual level, was 0.71 for BCSS in the entire cohort.

INTERPRETATION

Adjuvant! accurately predicted 10-year outcomes in this large-scale Dutch validation study and is of use for adjuvant treatment decision making, although the results may be less reliable in some subgroups.

The contribution of CHEK2 to the TP53-negative Li-Fraumeni phenotype

BACKGROUND

CHEK2 has previously been excluded as a major cause of Li-Fraumeni syndrome (LFS). One particular CHEK2 germline mutation, c.1100delC, has been shown to be associated with elevated breast cancer risk. The prevalence of CHEK2*1100delC differs between populations and has been found to be relatively high in the Netherlands. The question remains nevertheless whether CHEK2 germline mutations contribute to the Li-Fraumeni phenotype.

METHODS

We have screened 65 Dutch TP53-negative LFS/LFL candidate patients for CHEK2 germline mutations to determine their contribution to the LFS/LFL phenotype.

RESULTS

We identified six index patients with a CHEK2 sequence variant, four with the c.1100delC variant and two sequence variants of unknown significance, p.Phe328Ser and c.1096-?_1629+?del.

CONCLUSION

Our data show that CHEK2 is not a major LFS susceptibility gene in the Dutch population. However, CHEK2 might be a factor contributing to individual tumour development in TP53-negative cancer-prone families.

Effects of lycopene on the insulin-like growth factor (IGF) system in premenopausal breast cancer survivors and women at high familial breast cancer risk

Insulin-like growth factor-I (IGF-I) is an important growth factor associated with increased risk of premenopausal breast cancer. We conducted a randomized, placebo-controlled, double-blind, crossover trial to evaluate whether tomato-derived lycopene supplementation (30 mg/day for 2 mo) decreases serum levels of total IGF-I in premenopausal women with 1) a history of breast cancer (n=24) or 2) a high familial breast cancer risk (n=36). Also, IGF binding protein (IGFBP) increasing effects were evaluated. Lycopene supplementation did not significantly alter serum total IGF-I and other IGF system components in the 2 study populations combined. However, statistically significant discordant results were observed between the 2 study populations (i.e., P<0.05 for total IGF-I, free IGF-I, and IGFBP-3). Total IGF-I and IGFBP-3 were increased in the breast cancer survivor population [total IGF-I=7.0%, 95% confidence interval (CI)= -0.2 to 14.3%; IGFBP-3=3.3%, 95% CI=0.7-6.0%), and free IGF-I was decreased in the family history population (-7.6%, 95% CI= -14.6 to -0.6%). This randomized controlled trial shows that 2 mo of lycopene supplementation has no effect on serum total IGF-I in the overall study population. However, lycopene effects were discordant between the 2 study populations showing beneficial effects in high-risk healthy women but not in breast cancer survivors.

Abstract 3696A: The detection and prediction of circulating tumor cells in breast cancer patients

The detection of circulating tumor cells (CTC) in the blood of cancer patients is a promising tool for risk stratification, treatment tailoring, and monitoring of the disease state. The current study aims to develop a QPCR-based detection platform for the semi-quantitation of tumor cell load in the peripheral blood of breast cancer patients by combining gene expression data from 4 tumor marker genes into a single index-score. From a cohort of 131 individuals, CTC index-score positivity, indicating tumor cell presence, was observed in 14 out of 16 (88%) metastatic patients, 16 out of 87 (18%) non-metastatic stage I-III patients, and 0 out of 28 (0%) healthy female controls. A previous study demonstrated that CTC index-score positivity in metastatic patients correlated to a significantly shorter time to disease progression. This CTC detection platform demonstrates high specificity (100%) and sensitivity (88%), and can be an effective clinical tool providing valuable prognostic information.

This CTC detection assay was subsequently compared to a CTC prediction assay developed using microarray expression data from the primary tumors of the patients from the same cohort. From 73 patients, a CTC predictive tumor profile was developed with the ability to distinguish those patients with a positive CTC QPCR index-score from those with a negative index-score with an average 83% internal cross-validation accuracy. When a small independent test set was assayed, those patients classified on the basis of their tumor gene expression as having a positive CTC QPCR score had a shorter interval to metastasis development (mean = 29.6 months) versus those predicted to have a negative score (mean = 51.4 months).

When the QPCR-based and microarray-based CTC assays were compared directly, and each in combination with the “70-gene prognosis signature” for distant metastasis prediction, the CTC predictive microarray assay was superior to the CTC QPCR assay both alone and in combination with the 70-gene profile for time interval to metastasis. This study demonstrates that a microarray model predictive of tumor cell dissemination has prognostic value and seems independent of other metastasis-predictive microarray profiles.

Microarray gene-expression profiling to predict lymph node metastasis in penile carcinoma

OBJECTIVE

To determine the value of gene-expression profiling as a predictor of the status of the regional nodes in patients with penile carcinoma.

PATIENTS AND METHODS

Tumour samples of 56 patients with penile squamous cell carcinoma were analysed for the gene expression on 35 k oligoarrays; 32 were from patients with histopathologically confirmed lymph node metastases and 24 from those with no lymph node involvement. The 56 patients were divided into a training and validation set. For the training set, 15 patients with histopathologically confirmed nodal metastases and 15 without were selected. The validation set consisted of the remaining 26 patients, containing 17 node-positive and nine with no nodal metastases.

RESULTS

A 44-probe classifier had the best performance within the training set; this classifier correctly assigned 29 of 30 specimens in the training set to the two outcome groups. In the validation set of 26 tumours, the classifier correctly assigned 14 of the 26 (54%) specimens to the two outcome groups. Of the 17 specimens with histologically confirmed nodal involvement, 12 were classified as node-positive and five as node-negative, resulting in a sensitivity of 71%. Of the nine specimens from node-negative patients, two were correctly classified as node-negative and seven as node positive, resulting in a specificity of 22%.

CONCLUSIONS

In this series, gene expression profiling did not produce a useful classifier to predict nodal involvement in patients with penile carcinoma.

An information-theoretic analysis of genetics, gender and age in cancer patients

Germline genetics, gender and hormonal-signaling pathways are all well described modifiers of cancer risk and progression. Although an improved understanding of how germline genetic variants interact with other cancer risk factors may allow better prevention and treatment of human cancer, measuring and quantifying these interactions is challenging. In other areas of research, Information Theory has been used to quantitatively describe similar multivariate interactions. We implemented a novel information-theoretic analysis to measure the joint effect of a high frequency germline genetic variant of the p53 tumor suppressor pathway (MDM2 SNP309 T/G) and gender on clinical cancer phenotypes. This analysis quantitatively describes synergistic interactions among gender, the MDM2 SNP309 locus, and the age of onset of tumorigenesis in p53 mutation carriers. These results offer a molecular and genetic basis for the observed sexual dimorphism of cancer risk in p53 mutation carriers and a model is proposed that suggests a novel cancer prevention strategy for p53 mutation carriers.

Towards an optimized platform for the detection, enrichment, and semi-quantitation circulating tumor cells

Metastasis describes the process of migration of a frequently clinically occult circulating tumor cell (CTC) from the primary lesion to a new location and the subsequent formation of an overt growth. We and others have shown that the detection and quantitation of these cells has significant prognostic value, however there still remains no consensus as to the optimal methods to achieve this. The work described herein therefore considered various techniques, from storage and sample processing to data acquisition and analysis, to find an optimal combination of methods for an effective and practical platform for the detection of CTCs in peripheral blood. A dual-antigen epithelial cell enrichment procedure followed by a multi-marker QPCR analysis demonstrated the highest sensitivity and specificity, with the ability to detect as few as 10 tumor cells from a background of 10(6) peripheral blood mononuclear cells. Using these techniques in conjunction with a quadratic linear discriminant analysis (QDA) resulted in a platform able to generate this data and then combine it a single score for each patient, in which positivity reflected tumor cell presence, and negativity represented tumor cell absence. This assay was able to correctly determine tumor cell presence or absence in 100% of healthy controls and 84% of metastatic patients in a validation cohort of 39 individuals. This platform represents a highly sensitive and specific assay which could augment current routine assays for CTCs in the clinic.

Two TP53 germline mutations in a classical Li-Fraumeni syndrome family

Li-Fraumeni syndrome (LFS) is an autosomal dominantly inherited cancer predisposition syndrome characterized by a combination of tumors including sarcoma, breast cancer, brain tumors, adrenocortical carcinoma and leukemia. Germline mutations in the tumor suppressor gene TP53 are associated with LFS. We present a family with LFS in which initially a novel germline TP53 intron 5 splice site mutation was found. A second germline TP53 mutation, the exon 7 Asn235Ser (704A-->G) mutation, was detected in this family through pre-symptomatic DNA testing. This latter mutation has been reported repeatedly in the literature as a pathogenic mutation involved in LFS. We provide evidence for pathogenicity of the novel intron 5 splice site mutation, whereas this evidence is lacking for the exon 7 Asn235Ser (704A-->G) mutation. Our findings emphasize the importance of performing additional tests in case of germline sequence variants with uncertain functional effects.

Isolated isoflavones do not affect the circulating insulin-like growth factor system in men at increased colorectal cancer risk

Epidemiological studies show that increased insulin-like growth factor (IGF)-I concentrations are related to increased colorectal cancer risk. A reduced colorectal cancer risk has been associated with isoflavones, which might affect the IGF-system because of their weak estrogenic activity. We conducted a randomized, placebo-controlled, double-blind crossover study to investigate the effect of an 8-wk isolated isoflavone supplementation (84 mg/d) on serum concentrations of total IGF-I, free IGF-I, total IGF-II, IGF binding protein (BP)-1, IGFBP-2, and IGFBP-3. Additionally, we investigated whether IGF-system component differences were related to concentrations of the more potent estrogenic isoflavone metabolite, equol. Our study population consisted of 37 men with a family history of colorectal cancer or a personal history of colorectal adenomas. Isoflavone supplementation did not significantly affect serum total IGF-I concentrations (relative difference between serum total IGF-I concentrations after isoflavone supplementation and after placebo: -1.3%, 95% CI -8.6 to 6.0%). Neither free IGF-I, nor total IGF-II, IGFBP-1, IGFBP-2, or IGFBP-3 concentrations were significantly altered. Interestingly, the change in serum IGF-I concentrations after isoflavone supplementation was negatively associated with serum equol concentrations (r=-0.49, P=0.002). In conclusion, isolated isoflavones did not affect the circulating IGF-system in a male high-risk population for colorectal cancer. However, to our knowledge, this is the first study that suggests isoflavones might have an IGF-I lowering effect in equol producers only. This underlines the importance of taking into account equol status in future isoflavone intervention studies.

Gene-expression and immunohistochemical study of specific T-cell subsets and accessory cell types in the transformation and prognosis of follicular lymphoma

PURPOSE

Despite the generally favorable clinical course in follicular lymphoma (FL), a minority of patients have a poor prognosis-with death within 3 years of diagnosis-most often due to transformation to aggressive disease.

PATIENTS AND METHODS

In this study, we analyzed the potential of predicting early transformation on the basis of gene expression and immunologic parameters in FL biopsy samples taken at diagnosis.

RESULTS

At the gene-expression level, FL is a highly uniform disease at the time of diagnosis, precluding the detection of sufficiently validated prognostic gene-expression profiles suitable for a clinical setting. Combinations of differentially expressed genes indicate that immunologic mechanisms play a differential role in the risk of early transformation. Using immunohistochemistry for specific cell populations, the spatial distribution to neoplastic follicles and the activation of CD4-positive T-helper cells (P = .002) and specifically T-helper 1 (P = .004) were shown to be highly discriminatory to predict early transformation. A role for functional modulation of follicular dendritic cells could also be supported (P = .04). Other cell populations, including CD68-positive macrophages and regulatory T cells, were not differentially present.

CONCLUSION

These results support the identification of FL as an immunologically functional disease in which an interaction of the tumor cells and the functional composition of the microenvironment determines the clinical behavior.

Concordance among gene-expression-based predictors for breast cancer

BACKGROUND

Gene-expression-profiling studies of primary breast tumors performed by different laboratories have resulted in the identification of a number of distinct prognostic profiles, or gene sets, with little overlap in terms of gene identity.

METHODS

To compare the predictions derived from these gene sets for individual samples, we obtained a single data set of 295 samples and applied five gene-expression-based models: intrinsic subtypes, 70-gene profile, wound response, recurrence score, and the two-gene ratio (for patients who had been treated with tamoxifen).

RESULTS

We found that most models had high rates of concordance in their outcome predictions for the individual samples. In particular, almost all tumors identified as having an intrinsic subtype of basal-like, HER2-positive and estrogen-receptor-negative, or luminal B (associated with a poor prognosis) were also classified as having a poor 70-gene profile, activated wound response, and high recurrence score. The 70-gene and recurrence-score models, which are beginning to be used in the clinical setting, showed 77 to 81 percent agreement in outcome classification.

CONCLUSIONS

Even though different gene sets were used for prognostication in patients with breast cancer, four of the five tested showed significant agreement in the outcome predictions for individual patients and are probably tracking a common set of biologic phenotypes.

A comparison of univariate and multivariate gene selection techniques for classification of cancer datasets

Background

Gene selection is an important step when building predictors of disease state based on gene expression data. Gene selection generally improves performance and identifies a relevant subset of genes. Many univariate and multivariate gene selection approaches have been proposed. Frequently the claim is made that genes are co-regulated (due to pathway dependencies) and that multivariate approaches are therefore per definition more desirable than univariate selection approaches. Based on the published performances of all these approaches a fair comparison of the available results can not be made. This mainly stems from two factors. First, the results are often biased, since the validation set is in one way or another involved in training the predictor, resulting in optimistically biased performance estimates. Second, the published results are often based on a small number of relatively simple datasets. Consequently no generally applicable conclusions can be drawn.

Results

In this study we adopted an unbiased protocol to perform a fair comparison of frequently used multivariate and univariate gene selection techniques, in combination with a ränge of classifiers. Our conclusions are based on seven gene expression datasets, across several cancer types.

Conclusion

Our experiments illustrate that, contrary to several previous studies, in five of the seven datasets univariate selection approaches yield consistently better results than multivariate approaches. The simplest multivariate selection approach, the Top Scoring method, achieves the best results on the remaining two datasets. We conclude that the correlation structures, if present, are difficult to extract due to the small number of samples, and that consequently, overly-complex gene selection algorithms that attempt to extract these structures are prone to overtraining.

Pulmonary squamous cell carcinoma following head and neck squamous cell carcinoma: metastasis or second primary?

PURPOSE

To distinguish a metastasis from a second primary tumor in patients with a history of head and neck squamous cell carcinoma and subsequent pulmonary squamous cell carcinoma.

EXPERIMENTAL DESIGN

For 44 patients with a primary squamous cell carcinoma of the head and neck followed by a squamous cell carcinoma of the lung, clinical data, histology, and analysis of loss of heterozygosity (LOH) were used to differentiate metastases from second primary tumors.

RESULTS

Clinical evaluation suggested 38 patients with metastases and 6 with second primaries. We developed a novel interpretation strategy based on biological insight and on our observation that multiple LOH on different chromosome arms are not independent. LOH analysis indicated metastatic disease in 19 cases and second primary squamous cell carcinoma in 24 cases. In one case, LOH analysis was inconclusive. For 25 patients, LOH supported the clinical scoring, and in 18 cases, it did not. These 18 discordant cases were all considered to be second primary tumors by LOH analysis.

CONCLUSIONS

A considerable number of squamous cell lung lesions (50% in this study), clinically interpreted as metastases, are suggested to be second primaries by LOH analysis. For these patients, a surgical approach with curative intent may be justified.

Gene expression profiling and breast cancer care: What are the potential benefits and policy implications?

PURPOSE

Gene expression profiling has been proposed as an alternative to clinical guidelines to identify high-risk patients for adjuvant chemotherapy. However, the outcomes associated with gene expression profiling are not clear, and guidelines for the appropriate use of genomic technologies have not been established.

METHODS

We developed a decision analytic model to evaluate the incremental cost and quality-adjusted life years of gene expression profiling versus NIH clinical guidelines in a hypothetical cohort of premenopausal early stage breast cancer patients 44 years of age. We conducted empirical analyses and identified literature-based data to inform the model, and performed probabilistic sensitivity analyses to evaluate uncertainty in the results. We interpreted the implications of our findings for treatment guidelines and policies.

RESULTS

Use of gene expression profiling resulted in an absolute 5% decrease in the proportion of cases of distant recurrence prevented, 0.21 fewer quality-adjusted life years, and a cost savings of USD 2882. The chosen test cutoff value to identify a tumor as poor prognosis and the cost of adjuvant chemotherapy were the most influential parameters in the analysis, but our findings did not change substantially in sensitivity analyses. Regardless of the test cutoff used to identify a poor prognosis tumor, the gene expression profiling assay studied in our analysis, at its current level of performance, did not attain the threshold sensitivity (95%) necessary to produce equal or greater quality-adjusted life years than NIH guidelines.

CONCLUSION

Although the use of gene expression profiling in breast cancer care holds great promise, our analysis suggests additional refinement and validation are needed before use in clinical practice.

A protocol for building and evaluating predictors of disease state based on microarray data

MOTIVATION

Microarray gene expression data are increasingly employed to identify sets of marker genes that accurately predict disease development and outcome in cancer. Many computational approaches have been proposed to construct such predictors. However, there is, as yet, no objective way to evaluate whether a new approach truly improves on the current state of the art. In addition no 'standard' computational approach has emerged which enables robust outcome prediction.

RESULTS

An important contribution of this work is the description of a principled training and validation protocol, which allows objective evaluation of the complete methodology for constructing a predictor. We review the possible choices of computational approaches, with specific emphasis on predictor choice and reporter selection strategies. Employing this training-validation protocol, we evaluated different reporter selection strategies and predictors on six gene expression datasets of varying degrees of difficulty. We demonstrate that simple reporter selection strategies (forward filtering and shrunken centroids) work surprisingly well and outperform partial least squares in four of the six datasets. Similarly, simple predictors, such as the nearest mean classifier, outperform more complex classifiers. Our training-validation protocol provides a robust methodology to evaluate the performance of new computational approaches and to objectively compare outcome predictions on different datasets.

Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival

Based on the hypothesis that features of the molecular program of normal wound healing might play an important role in cancer metastasis, we previously identified consistent features in the transcriptional response of normal fibroblasts to serum, and used this "wound-response signature" to reveal links between wound healing and cancer progression in a variety of common epithelial tumors. Here, in a consecutive series of 295 early breast cancer patients, we show that both overall survival and distant metastasis-free survival are markedly diminished in patients whose tumors expressed this wound-response signature compared to tumors that did not express this signature. A gene expression centroid of the wound-response signature provides a basis for prospectively assigning a prognostic score that can be scaled to suit different clinical purposes. The wound-response signature improves risk stratification independently of known clinico-pathologic risk factors and previously established prognostic signatures based on unsupervised hierarchical clustering ("molecular subtypes") or supervised predictors of metastasis ("70-gene prognosis signature").

Comparative Genomic Hybridization Profiles in Human BRCA1 and BRCA2 Breast Tumors Highlight Differential Sets of Genomic Aberrations

BRCA1 or BRCA2 germline mutations cause ∼30% of breast cancers within high-risk families. This represents 5% of total breast cancer incidence. Although BRCA1 and BRCA2 are both implicated in DNA repair and genome stability, it is unknown whether BRCA1 and BRCA2 are associated with similar or distinct diseases. In a previous study we reported that BRCA1-related breast carcinomas show a distinct genomic profile as determined by comparative genomic hybridization (CGH). We now hypothesize that, if functionally equivalent, mutations in BRCA1 and BRCA2 would result in similar genomic profiles in tumors. Here we report the chromosomal gains and losses as measured by CGH in 25 BRCA2-associated breast tumors and compared them with our existing 36 BRCA1 and 30 control profiles. We compared all chromosomal regions and determined the regions of differential gain or loss between tumor classes and controls. BRCA2 and control tumors have very similar genomic profiles. As a consequence, and in contrast to BRCA1-associated tumors, CGH profiles from BRCA2-associated tumors could not be distinguished from control tumors using the classification methodology as we have developed before. The largest number of significant differences existed between BRCA1 and controls, followed by BRCA1 compared with BRCA2, suggesting different tumor development pathways for BRCA1 and BRCA2.

Comparative genomic hybridization profiles in human BRCA1 and BRCA2 breast tumors highlight differential sets of genomic aberrations

BRCA1 or BRCA2 germline mutations cause approximately 30% of breast cancers within high-risk families. This represents 5% of total breast cancer incidence. Although BRCA1 and BRCA2 are both implicated in DNA repair and genome stability, it is unknown whether BRCA1 and BRCA2 are associated with similar or distinct diseases. In a previous study we reported that BRCA1-related breast carcinomas show a distinct genomic profile as determined by comparative genomic hybridization (CGH). We now hypothesize that, if functionally equivalent, mutations in BRCA1 and BRCA2 would result in similar genomic profiles in tumors. Here we report the chromosomal gains and losses as measured by CGH in 25 BRCA2-associated breast tumors and compared them with our existing 36 BRCA1 and 30 control profiles. We compared all chromosomal regions and determined the regions of differential gain or loss between tumor classes and controls. BRCA2 and control tumors have very similar genomic profiles. As a consequence, and in contrast to BRCA1-associated tumors, CGH profiles from BRCA2-associated tumors could not be distinguished from control tumors using the classification methodology as we have developed before. The largest number of significant differences existed between BRCA1 and controls, followed by BRCA1 compared with BRCA2, suggesting different tumor development pathways for BRCA1 and BRCA2.

The insulin-like growth factor system in cancer prevention: potential of dietary intervention strategies

The insulin-like growth factor (IGF) system is related to proliferation and tumor growth, and high levels of circulating IGF-I are thought to be a risk factor for several types of cancer. This review summarizes the epidemiologic evidence for an association between circulating IGF-I and cancer risk as well as the experimental evidence for a causal relation between the endocrine IGF system and tumor growth. The potential for dietary intervention to alter the IGF system and thereby cancer risk is supported by several lines of evidence. Postulated mechanisms of action are as follows: (a) reduction of levels of circulating IGF-I, which will decrease activation of the IGF-I receptor and subsequent signaling pathways; (b) increasing local IGF binding proteins, which may have IGF-dependent effects through obstruction of IGF interaction with local IGF-I receptor as well as IGF-independent effects; and (c) interference with estrogens and estrogen receptor action, which may have direct (and possibly synergistic) effects on IGF signaling. An overview is given of the epidemiologic studies on dietary determinants of circulating IGF-I. Examples of dietary factors, such as dairy protein, lycopene, and phytoestrogens, are used to illustrate the potential mode of action of dietary interventions that may act on the IGF system. In conclusion, the IGF system has every potential to serve as an intermediate for cancer (chemo)prevention studies. On the short term, more research initiatives aimed at the effects of specific food components or dietary strategies on the IGF system both in animal models and in humans are warranted.

Gene expression profiling in follicular lymphoma to assess clinical aggressiveness and to guide the choice of treatment

Follicular lymphoma (FL) is a disease characterized by a long clinical course marked by frequent relapses that vary in clinical aggressiveness over time. Therefore, the main dilemma at each relapse is the choice for the most effective treatment for optimal disease control and failure-free survival while at the same time avoiding overtreatment and harmful side effects. The selection for more aggressive treatment is currently based on histologic grading and clinical criteria; however, in up to 30% of all cases these methods prove to be insufficient. Using supervised classification on a training set of paired samples from patients who experienced either an indolent or aggressive disease course, a gene expression profile of 81 genes was established that could, with an accuracy of 100%, distinguish low-grade from high-grade disease. This profile accurately classified 93% of the FL samples in an independent validation set. Most important, in a third series of FL cases where histologic grading was ambiguous, precluding meaningful morphologic guidance, the 81-gene profile shows a classification accuracy of 94%. The FL stratification profile is a more reliable marker of clinical behavior than the currently used histologic grading and clinical criteria and may provide an important alternative to guide the choice of therapy in patients with FL both at presentation and at relapse.

Hard-wired genotype in metastatic breast cancer

Recently, we showed by gene-expression profiling that the molecular program established in a human primary breast carcinoma is highly preserved in its distant metastases. According to the predominant model of metastasis, the capacity of a primary tumor to metastasize is acquired only rarely and late in tumorigenesis. Our findings challenge this common theory and imply that the metastatic nature of 'poor prognosis profile' breast carcinomas is an inherent feature, and not reserved to advantageous subpopulations.

Excess risk for contralateral breast cancer in CHEK2*1100delC germline mutation carriers

We detected a significant excess risk for CHEK2*1100delC mutation carriers to develop a contralateral breast tumor, OR = 6.5 (95% CI 1.5-28.8, p = 0.005). The highest percentage of mutation carriers was detected among those bilateral breast cancer patients who had received radiation treatment for their first breast tumor. These results warrant prolonged medical surveillance and may indicate a clinically important interaction between CHEK2 heterozygosity and radiation in the development of contralateral breast cancer.

Gene expression profiles of primary breast tumors maintained in distant metastases

It has been debated for decades how cancer cells acquire metastatic capability. It is unclear whether metastases are derived from distinct subpopulations of tumor cells within the primary site with higher metastatic potential, or whether they originate from a random fraction of tumor cells. Here we show, by gene expression profiling, that human primary breast tumors are strikingly similar to the distant metastases of the same patient. Unsupervised hierarchical clustering, multidimensional scaling, and permutation testing, as well as the comparison of significantly expressed genes within a pair, reveal their genetic similarity. Our findings suggest that metastatic capability in breast cancer is an inherent feature and is not based on clonal selection.