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Purpose: Most hormone receptor (HR)+/HER2− breast cancer patients respond unfavorably to neoadjuvant chemotherapy (NAC); however, genomic tests may identify those patients who are likely to benefit. Using the Prosigna assay, we first evaluated the technical performance of core needle biopsy (CNB) tissues. We then determined whether Prosigna risk of relapse (ROR) score and intrinsic subtype predicted response to NAC in HR+/HER2− patients using CNB samples.Experimental Design: Using the NanoString's nCounter Dx analysis system and a development tissue sample set, we established tissue requirements and assay output variance. We then evaluated the concordance in subtype and correlation in ROR between CNBs and corresponding surgical resection specimens (SRS) in a second independent sample set. Finally, we analyzed 180 independent CNB samples from HR+/HER2− patients who were treated with NAC and correlated ROR and intrinsic subtype with pathologic response.Results: Intra- and interbiopsy variabilities were 2.2 and 6.8 ROR units, respectively. Subtype concordance within multiple CNBs was high for the 4- and 3-subtype classifications (k = 0.885 and 0.889, respectively). Correlation in Prosigna ROR score observed between paired CNBs and SRS was high (r ≥ 0.90), and subtype concordance was also high for the 4- and 3-subtype classifications (kappa = 0.81 and 0.91, respectively). Prosigna results obtained from the HR+/HER2− patient samples showed that both ROR (P = 0.047) and intrinsic subtype (OR LumA vs. non-LumA = 0.341, P = 0.037) were significant predictors of response to NAC.Conclusions: Prosigna ROR and intrinsic subtype are readily obtained from CNB samples in normal practice and reliably predict response to NAC in HR+/HER2− patients. Clin Cancer Res; 22(3); 560–6. ©2015 AACR.

Tolerability of molecularly targeted agents (MTA) used in cancer therapeutics is determined in phase I trials. We reviewed the reported incidence of toxicity in phase III trials at doses and schedules recommended by phase I trials to evaluate whether these recommendations are realistic when drugs are used in larger populations of patients. We systematically reviewed a safety profile of small molecule (SM-MTA) and mAb MTA (MA-MTA) approved by the FDA in the last 12 years. There was a significantly increased percentage of grade 3 or 4 adverse events reported with SM-MTA compared with MA-MTA [40% vs. 27%; RR 1.5; 95% confidence interval (CI), 1.10–2.25, P = 0.038] in phase III studies. Importantly, a substantial proportion of patients (45%) treated with SM-MTA required dose modifications due to drug-related toxicity in phase III trials. However, this toxicity was associated to a definitive study drug discontinuation in only 9%. Overall, 25% of SM-MTA declared recommended phase II doses below MTD based on pharmacokinetic–pharmacodynamic data and these trials were associated with a significantly reduced number of dose modifications in registration trials (32% vs. 50%; RR 0.64; 95% CI, 0.43–0.88, P = 0.01). Tolerability is going to come into further focus due to the need for combinations of SM-MTA and other anticancer agents. There was a higher incidence of grade 3–4 toxicity in phase III trials in combinations versus single-agent SM-MTAs (64% vs. 37%; RR 1.73; 95% CI, 1.3–2.3, P = 0.001). These results indicate that phase I studies underestimate toxicity while recommending doses of SM-MTA. Clin Cancer Res; 22(9); 2127–32. ©2015 AACR.

Supplemental Methods, Tables and Figures Tables Table S1. CES association with chemotherapy sensitivity (measured as pCR) in the MDACC-based dataset. Table S2. CES association with chemotherapy sensitivity (measured as Residual Cancer Burden [RCB]) in the MDACC-based dataset. Model A. Table S3. CES association with chemotherapy sensitivity (measured as Residual Cancer Burden [RCB]) in the MDACC-based dataset. Model B. Table S4. Univariate association of CES and various signatures with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S5. Association of CES and PAM50 Proliferation Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S6. Association of CES and CHEMOPRED Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S7. Association of CES and the proliferation component of the Genomic Health Index (GHI; OncotypeDX Recurrence Score) with chemotherapy sensitivity in HR+/HER2- negative disease from the MDACC-based dataset. Table S8. Association of CES and Genomic Grade Index (GGI) Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S9. Association of CES and SET index Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S10. Association of CES and RCBPRED Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S11. Association of CES and DLDA30 Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S12. Association of CES and ROR-P Signature with chemotherapy sensitivity in HR+/HER2-negative disease from the MDACC-based dataset. Table S13. Association of CES and Ki67 by IHC with chemotherapy sensitivity in HR+/HER2-negative disease of the Malaga cohort. 7 Table S14. Association of CES and PAM50 ROR with chemotherapy sensitivity in HR+/HER2-negative disease of the Malaga cohort. Table S15. CES association with endocrine sensitivity in the Marsden dataset (n=103). Table S16. CES association with endocrine sensitivity in the Marsden dataset within HER2-negative disease (n=89). Figures Fig. S1. Association of CES with Miller-Payne following chemotherapy in HR+/HER2- negative disease from the Malaga-based cohort. Fig. S2. CES association with endocrine sensitivity in the Edinburgh dataset (n=120). (A) Tumor volume changes of each patient and response classification. (B) Association of CES and other variables with response (defined as at least 70% reduction by 90 days) in the overall population. (C) Association of CES and other variables with response within HER2-negative disease. Fig. S3. Association of CES with pCR in the combined dataset from the MDACC- and Malaga-based cohorts.

Supplementary Figure S1 and Supplementary Tables S1-S2. Supplementary Figure S1. Diagram of tissue block usage for CNB Development Study and Chemo-prediction Validation Study. Supplemental Table S1. Top-10 and bottom-10 Prosigna gene-correlations between paired CNBs and SRS. Supplemental Table S2. Distribution of the Prosigna subtypes within the three main pathology-based groups in 39 independent metastatic samples.

Purpose: Hormone receptor–positive (HR+) breast cancer is clinically and biologically heterogeneous, and subgroups with different prognostic and treatment sensitivities need to be identified.Experimental Design: Research-based PAM50 subtyping and expression of additional genes was performed on 63 patients with HR+/HER2− disease randomly assigned to neoadjuvant multiagent chemotherapy versus endocrine therapy in a phase II trial. The biology associated with treatment response was used to derive a PAM50-based chemoendocrine score (CES). CES's predictive ability was evaluated in 4 independent neoadjuvant data sets (n = 675) and 4 adjuvant data sets (n = 1,505). The association of CES, intrinsic biology, and PAM50 risk of relapse (ROR) was explored across 6,007 tumors.Results: Most genes associated with endocrine sensitivity were also found associated with chemotherapy resistance. In the chemotherapy test/validation data sets, CES was independently associated with pathologic complete response (pCR), even after adjusting for intrinsic subtype. pCR rates of the CES endocrine–sensitive (CES-E), uncertain (CES-U), and chemotherapy-sensitive (CES-C) groups in both data sets combined were 25%, 11%, and 2%, respectively. In the endocrine test/validation data sets, CES was independently associated with response. Compared with ROR, >90% of ROR-low and ROR-high tumors were identified as CES-E and CES-C, respectively; however, each CES group represented >25% of ROR-intermediate disease. In terms of survival outcome, CES-C was associated with poor relapse-free survival in patients with ROR-intermediate disease treated with either adjuvant endocrine therapy only or no adjuvant systemic therapy, but not in patients treated with (neo)adjuvant chemotherapy.Conclusions: CES is a genomic signature capable of estimating chemoendocrine sensitivity in HR+ breast cancer beyond intrinsic subtype and risk of relapse. Clin Cancer Res; 23(12); 3035–44. ©2016 AACR.

Detailed description of phase I and registration trials for each approved small molecule. Dose and schedule developed will be specified, along with dose modifications due to toxicity.

Background CDK4/6 inhibitors plus endocrine therapies are the current standard of care in the first-line treatment of HR+/HER2-negative metastatic breast cancer, but there are no well-established clinical or molecular predictive factors for patient response. In the era of personalised oncology, new approaches for developing predictive models of response are needed. Materials and methods Data derived from the electronic health records (EHRs) of real-world patients with HR+/HER2-negative advanced breast cancer were used to develop predictive models for early and late progression to first-line treatment. Two machine learning approaches were used: a classic approach using a data set of manually extracted features from reviewed (EHR) patients, and a second approach using natural language processing (NLP) of free-text clinical notes recorded during medical visits. Results Of the 610 patients included, there were 473 (77.5%) progressions to first-line treatment, of which 126 (20.6%) occurred within the first 6 months. There were 152 patients (24.9%) who showed no disease progression before 28 months from the onset of first-line treatment. The best predictive model for early progression using the manually extracted dataset achieved an area under the curve (AUC) of 0.734 (95% CI 0.687–0.782). Using the NLP free-text processing approach, the best model obtained an AUC of 0.758 (95% CI 0.714–0.800). The best model to predict long responders using manually extracted data obtained an AUC of 0.669 (95% CI 0.608–0.730). With NLP free-text processing, the best model attained an AUC of 0.752 (95% CI 0.705–0.799). Conclusions Using machine learning methods, we developed predictive models for early and late progression to first-line treatment of HR+/HER2-negative metastatic breast cancer, also finding that NLP-based machine learning models are slightly better than predictive models based on manually obtained data.

Breast cancer (BC) is the most frequent neoplasia affecting women worldwide normally detected at early stages. In this regard, early diagnosis drastically decreases mortality, however, around 20% of these patients will later relapse. This is mainly caused by undetectable molecular residual disease (MRD) not eliminated by standard primary treatments. Therefore, it is crucial to detect the after-treatment MRD to stratify the patients by their risk of relapse. Liquid biopsies have emerged as non-invasive method to obtain information about tumors and improve clinical cancer management. Regarding this, much has been hypothesized about utilizing high blood volumes to overcome the necessity of complex and resource-intensive next generation sequencing (NGS) methodologies to detect highly diluted blood tumor components in localized cancers. Herein, we employed a combined analysis of circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) together with high blood volumes and single-assay droplet digital PCR (ddPCR) to detect MRD with ultra-high sensitivity. We prospectively assayed 124 samples extracted at baseline, post-neoadjuvant therapy (NAT), post-surgery and a follow-up on a six-monthly basis. A median of 76.40 mL of blood to detect CTCs and 40 mL of plasma to detect ctDNA per patient from 19 BC women were used in this study. ddPCR assays were performed with a median of 14 partitions per determination to detect ctDNA and 12 partitions for CTCs. Overall, ctDNA, CTCs and ctDNA and/or CTCs were detected in 84.21%, 66.66% and 89.47% respectively in the pre-treatment blood samples. MRD (ctDNA and/or CTCs) was detected in 73.68% of the after NAT blood samples. On the other hand, it was detected in 46.66% and 70.00% of the post-surgery and follow-up samples respectively. Post-NAT MRD was detected in 57.14% (4/7) and 83.33% (10/12) of patients with and without pathological complete response pCR respectively. To note, the discordant patients achieving pCR in tissue with detectable MRD in blood were high-risk BC. Importantly, in one of the two patients without pCR and no MRD detected, not enough sample were available to complete the analysis. The other discordant patient presented a localized disease with residual cancer burden value of 1 and no lymph nodes affected. In 1 out of 19 (5.26%) patient clinically relapsed with a positive MRD detection 6 months earlier. Applying this methodology, we observed a sensitivity of 0.004% in ctDNA detection and 0.224 CTCs per mL of blood. Overall, this novel methodology greatly improves sensitivity for ctDNA and CTCs detection in treatment-naïve early BC. In addition, MRD was successfully detected in post-treatment samples antedating clinical relapse by 6 months in one patient. This prospective study is potentially demonstrating that using high blood volumes and a single-assay ddPCR is a cost-effective strategy to monitor localized BC and predict relapses. Citation Format: Alfonso Alba-Bernal, Ana Godoy-Ortiz, María Emilia Domínguez-Recio, Begoña Jimenez-Rodriguez, María Elena Quirós-Ortega, Esperanza López-López, Guillermo Carbajosa-Antona, Jesús Peralta-Linero, Luis Vicioso, Estefanía Bellagarza-García, Guadalupe Dolores Garrido-Ruiz, Cynthia Robles-Podadera, Alicia Garrido-Aranda, María Dunia Roldán-Díaz, Jesús Velasco-Suelto, Rocío Lavado-Valenzuela, Martina Álvarez, Nuria Ribelles, Javier Pascual, Emilio Alba, Iñaki Comino-Méndez. Increasing blood volumes to detect minimal residual disease in neoadjuvant-treated early breast cancer patients. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6610.

Introduction: While pCR has been amply associated with improved treatment outcome in patients treated with NAC and surgery, there are only few studies that explore the molecular determinants of pCR. Given the discrete percentage of patients who achieve pCR after NAC, it is of upmost need to identify biomarkers that can discern between responder and non-responder patients before NAC and therefore determine the best therapeutic approach in advance. Our aim is to find the best combination of variables to predict pCR in our cohort. Patients: To evaluate if there is a gene expression profile that could predict pathological complete response (pCR) to NAC, we selected a cohort of 69 patients treated with neoadjuvant chemotherapy consisting of anthracyclines + taxanes; HER2+ patients were further treated with trastuzumab. The median age was 48 years, and 71% of patients were premenopausal. The median of mammographic tumor size was 3,7. Most patients (89%) had invasive ductal carcinoma, and the histological grade was mainly 2 (55,7% Grade 1+2; 44,3% Grade 3). ER and PR positivity were seen in 63% and 53% of cases respectively. HER2 overexpression was seen in 20% of tumors. Methods: Gene expression was evaluated in 770 genes involved in 13 canonical cancer pathways as screened with the nCounter® PanCancer Pathways panel in FFPE pre-treatment tumor biopsies and analyzed with the nSolverTM software. The collected clinical and pathologic variables were age, mammographic tumor size, nodal status, tumor grade, HR status, HER2-overexpression, Ki67 percentage, IHQ subtype and PAM50 subtype. Finally, LASSO regression was used to predict pCR based on normalized gene expression levels and clinical and pathological data. Results: Out of the 69 enrolled patients, 27 achieved pCR (39%) and 42 did not (determined by Miller and Payne criteria). High-quality RNA was isolated from each patient for doing Nanostring nCounter experiment. Based on the gene expression levels of the PanCancer Pathways panel, Lasso regression identified a subset of genes as predictive of pCR. Therefore, the combination of expression levels of DTX3, CACNA1G, IL11, ETV4 and TSPAN7 genes, predicted pCR with an average 70% of Area Under the Curve ROC (AUC) on the test set in a cross-validation scheme. DTX3 is a member of Notch pathway, IL11 from JAK-STAT pathway, CACNA1G from MAPK pathway, ETV4 and TSPAN7 from Transcriptional misregulation pathway. DTX3, CACNA1G and TSPAN7 are down-regulated and IL11 and ETV4 are up-regulated in patients who achieved pCR. Regarding the clinical and pathological data, the best model for predict pCR obtained an 60% of AUC and the selected variables were age, mammographic tumor size, nodal status, tumor grade and Ki67 percentage. Conclusions: In our cohort, the combination of gene expression levels of DTX3, CACNA1G, IL11, ETV4 and TSPAN7 can predict tumor response to NAC even better than any clinical or pathological variable. Although validation in a separate cohort is necessary, our results indicate that this combination could constitute a predictive gene signature to discriminate resistant patients to NAC before the treatment in breast cancer tumors. Citation Format: Maria Rosario Chica-Parrado, Julio Montes-Torres, Cynthia Robles-Podadera, Martina Alvarez, Jose Jerez, Luis Vicioso, Lidia Pérez-Villa, Begoña Jimenez, Nuria Ribelles, Ana Godoy, Isabel Barragán-Mallofret, Emilio Alba. Gene expression levels of DTX3, CACNA1G, IL11, ETV4 and TSPAN7 selected by LASSO penalty regression could predict pCR after neoadjuvant chemotherapy in breast cancer tumors [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 P1-10-26.

The COVID-19 pandemic has caused a profound change in health organizations at both the primary and hospital care levels. This cross-sectional study aims to investigate the impact of the COVID-19 pandemic in the annual rate of new cancer diagnosis in two university-affiliated hospitals. This study includes all the patients with a pathological diagnosis of cancer attended in two hospitals in Málaga (Spain) during the first year of pandemic. This study population was compared with the patients diagnosed during the previous year 2019. To analyze whether the possible differences in the annual rate of diagnoses were due to the pandemic or to other causes, the patients diagnosed during 2018 and 2017 were also compared. There were 2340 new cancer diagnosis compared to 2825 patients in 2019 which represented a decrease of −17.2% (p = 0.0001). Differences in the number of cancer patients diagnosed between 2018 and 2019 (2840 new cases, 0.5% increase) or 2017 and 2019 (2909 new cases, 3% increase) were not statistically significant. The highest number of patients lost from diagnosis in 2020 was in breast cancer (−26.1%), colorectal neoplasms (−16.9%), and head and neck tumors (−19.8%). The study of incidence rates throughout the first year of the COVID-19 pandemic shows that the diagnosis of new cancer patients has been significantly impaired. Health systems must take the necessary measures to restore pre-pandemic diagnostic procedures and to recover lost patients who have not been diagnosed.

Background: Dostarlimab is a programmed death 1 (PD-1) inhibitor approved as monotherapy in pts with dMMR recurrent/advanced endometrial cancer (EC) that has progressed on or following treatment with a platinum-containing regimen or solid tumors that have progressed on or following prior treatment, with no satisfactory alternative treatment options. Here we report on a post-hoc analysis of antitumor activity by PDL1 expression and TMB in pts with dMMR and MMRp solid tumors in the GARNET trial. Methods: GARNET (NCT02715284) is a phase 1, multicenter, open-label, single-arm study of dostarlimab in pts with advanced/recurrent solid tumors. Three expansion cohorts enrolled pts based on MMR status: dMMR (A1) and MMRp (A2) advanced/recurrent EC, and dMMR non-EC solid tumors (F). Pts received dostarlimab 500 mg IV Q3W for 4 cycles, then 1000 mg IV Q6W until progression or discontinuation. TMB and PDL1 were exploratory biomarkers. TMB status was determined by Foundation One test; TMB-high (TMB-H) was defined as ≥10 mutations/Mb. PDL1 expression was determined by combined positive score (CPS) by Ventana assay; PDL1-high (PDL1-H) was defined as CPS ≥1. The study was not powered to assess antitumor activity within subgroups. Results: TMB-H and PDL1-H were common in dMMR solid tumors; PDL1-H was observed in 39.4% of MMRp EC tumors (Table). Objective response rate (ORR) was higher in pts with TMB-H/PDL1-H tumors (55.6% for all cohorts, combined; Table). Safety for each cohort was previously reported.1 Conclusions: PDL1-H and TMB-H were frequently observed in the dMMR EC and non-EC cohorts, regardless of tumor type; PDL1-H was also prevalent in MMRp EC tumors. Although not powered to assess antitumor activity, ORR by BICR per RECIST v1.1 was higher in pts with TMB-H and PDL1-H solid tumors. Across cohorts, dMMR status was predictive of response. 1.Andre T, et al. Ann Oncol 2021;32(suppl 5):S829-S866. 991P. Table A1(dMMR EC)N=103 F(dMMR non-EC)N=106 A1+F(dMMR combined)N=209 A2(MMRp EC)N=142 A1+A2+F (Total)N=351 Biomarker distribution, n (%) TMB High 85 (82.5) 79 (74.5) 164 (78.5) 9 (6.3) 173 (49.3) Low 13 (12.6) 9 (8.5) 22 (10.5) 129 (90.8) 151 (43.0) Unknown 5 (4.9) 18 (17.0) 23 (11.0) 4 (2.8) 27 (7.7) PD-L1 High 56 (54.4) 52 (49.1) 108 (51.7) 56 (39.4) 164 (46.7) Low 23 (22.3) 17 (16.0) 40 (19.1) 45 (31.7) 85 (24.2) Unknown 24 (23.3) 37 (34.9) 61 (29.2) 41 (28.9) 102 (29.1) ORR by BICR per RECIST v1.1, n/N (%, 95% CI)a Overall 46/103(44.7, 34.9–54.8) 41/106(38.7, 29.4–48.6) 87/209(41.6, 34.9–48.6) 19/142(13.4, 8.3–20.1) — TMB-L/PDL1-L (L/L) 1/5(20.0, 0.5–71.6) 1/3 (33.3, 0.8–90.6) 2/8(25.0, 3.2–65.1) 2/43(4.7, 0.6–15.8) 4/51(7.8, 2.2–18.9) TMB-L/PDL1-H (L/H) 2/5(40.0, 5.3–85.3) 1/2(50.0, 1.3–98.7) 3/7(42.9, 9.9–81.6) 7/50(14.0, 5.8–26.7) 10/57(17.5, 8.7–29.9) TMB-H/PDL1-L (H/L) 5/17(29.4, 10.3–56.0) 3/14(21.4, 4.7–50.8) 8/31(25.8, 11.9–44.6) 0/1(0, 0–97.5) 8/32(25.0, 11.5–43.4) TMB-H/PDL1-H (H/H) 29/50(58.0, 43.2–71.8) 22/43(51.2, 35.5–66.7) 51/93(54.8, 44.2–65.2) 4/6(66.7, 22.3–95.7) 55/99(55.6, 45.2–65.5) aOnly those pts with both known TMB status and known CPS were included in ORR calculations Citation Format: Thierry André, Susana Banerjee, Dominique Berton, Susan L. Ellard, Begoña Jimenez, Vanessa Samouëlian, Lucy Gilbert, Valentina Boni, Xinwei Han, Grace Antony, Jennifer Veneris, Ana Oaknin. Antitumor activity of dostarlimab by PD-L1 and tumor mutation burden (TMB) in patients (pts) with mismatch repair deficient and proficient (dMMR and MMRp) tumors in the GARNET trial [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5135.

Breast cancer is the most common cancer type in women worldwide and its early detection is crucial to curing the disease. Tissue biopsy, currently the method of choice to obtain tumour molecular information, is invasive and might be affected by tumour heterogeneity rendering it incapable to portray the complete molecular picture. Liquid biopsy permits to study disease features in a more comprehensive manner by sampling biofluids and extracting tumour components such as circulating-tumour DNA (ctDNA), circulating-tumour cells (CTCs), and/or circulating-tumour RNA (ctRNA) amongst others in a monitoring-compatible manner. In this review, we describe the recent progress in the utilization of the circulating tumour components using early breast cancer samples. We review the most important analytes and technologies employed for their study.

Simple Summary In this review we discuss the recent knowledge about the role of breast and gut microbiome in the pathogenesis of breast cancer. We examine the proposed mechanisms of interaction between breast tumors and the microbiome. We focus on the role of the microbiome in: (i) the development and maintenance of estrogen metabolism through bacterial beta-glucuronidase enzymes (ii) the regulation of the host´s immune system and tumor immunity by Treg lymphocyte proliferation through bacterial metabolites such as butyrate and propionate (SCFAs), (iii) the induction of chronic inflammation, (iv) the response and/or resistance to treatments and (v) the epigenetic reprogramming. Moreover, we also discuss that diet, probiotics and prebiotics could exert important anticarcinogenic effects in breast cancer that could indicate their employment as adjuvants in standard-of-care breast cancer treatments. Overall, these findings could give new insights for building up novel strategies for breast cancer prevention and treatment. Abstract In breast cancer (BC) the employment of sequencing technologies for metagenomic analyses has allowed not only the description of the overall metagenomic landscape but also the specific microbial changes and their functional implications. Most of the available data suggest that BC is related to bacterial dysbiosis in both the gut microenvironment and breast tissue. It is hypothesized that changes in the composition and functions of several breast and gut bacterial taxa may contribute to BC development and progression through several pathways. One of the most prominent roles of gut microbiota is the regulation of steroid-hormone metabolism, such as estrogens, a component playing an important role as risk factor in BC development, especially in postmenopausal women. On the other hand, breast and gut resident microbiota are the link in the reciprocal interactions between cancer cells and their local environment, since microbiota are capable of modulating mucosal and systemic immune responses. Several in vivo and in vitro studies show remarkable evidence that diet, probiotics and prebiotics could exert important anticarcinogenic effects in BC. Moreover, gut microbiota have an important role in the metabolism of chemotherapeutic drugs and in the activity of immunogenic chemotherapies since they are a potential dominant mediator in the response to cancer therapy. Then, the microbiome impact in BC is multi-factorial, and the gut and breast tissue bacteria population could be important in regulating the local immune system, in tumor formation and progression and in therapy response and/or resistance.

Neoadjuvant Chemotherapy (NAC) in Breast Cancer (BC) has proved useful for the reduction in tumor burden prior to surgery, allowing for a more extensive breast preservation and the eradication of subjacent micrometastases. However, the impact on prognosis is highly dependent on the establishment of Pathological Complete Response (pCR), in particular for Triple Negative (TN) and Hormonal Receptor negative/Human Epidermal growth factor Receptor 2 positive (HR−/HER2+) subtypes. Several pCR predictors, such as PAM50, Integrative Cluster (IntClust), mutations in PI3KCA, or the Trastuzumab Risk model (TRAR), are useful molecular tools for estimating response to treatment and are prognostic. Major evolution events during BC NAC that feature the Residual Disease (RD) are the loss of HR and HER2, which are prognostic of bad outcome, and stemness and immune depletion-related gene expression aberrations. This dynamic nature of the determinants of response to BC NAC, together with the extensive heterogeneity of BC, raises the need to discern the individual and subtype-specific determinants of resistance. Moreover, refining the current approaches for a comprehensive monitoring of tumor evolution during treatment, RD, and eventual recurrences is essential for identifying new actionable alterations and the integral best management of the disease.

Concurrent radio-chemotherapy (RT-CT) is the standard treatment for locally advanced head and neck squamous cell carcinoma (LA-HNSCC), but RT plus epidermal growth factor receptor (EGFR) inhibitors is an effective option when CT is not appropriate. Human papillomavirus (HPV) is associated with an improved prognosis in LA-HNSCC; however, it has not been fully studied as a prognostic factor after RT + EGFR inhibitors. Immunohistochemical expression of p16INK4A and PCR of HPV16 DNA were retrospectively analyzed in tumor blocks from 52 stage III/IV LA-HNSCC patients treated with RT + EGFR inhibitors. Disease-free survival (DFS) and overall survival (OS) were analyzed by the Kaplan–Meier method. DNA of HPV16 was found in six of 52 tumors (12 %) and p16 positivity in eight tumors (15 %). After a median follow-up time of 45 months (6–110), p16-positive patients treated with RT + EGFR inhibitors showed an improved DFS (2-year DFS 75 vs. 44 %, HR 0.25, 95 % CI 0.06–0.99, p = 0.047) compared with p16-negative patients. These differences were outperformed when compared by HPV16 status (2-year OS rates of 83 vs. 58 %, HR 0.17, 95 % CI 0.02–0.99, p = 0.049 and 2-year DFS rates of 83 vs. 45 %, HR 0.17, 95 % CI 0.02–0.99, p = 0.049). In the Cox regression analysis with OS as the end point, ECOG 0–1 was the only prognostic factor independently associated with a good prognosis in the multivariable analysis. In this study, p16/HPV16-positive patients with LA-HNSCC treated with RT + EGFR inhibitors showed a better survival, not confirmed in multivariate analysis.

Purpose: Hormone receptor–positive (HR+) breast cancer is clinically and biologically heterogeneous, and subgroups with different prognostic and treatment sensitivities need to be identified. Experimental Design: Research-based PAM50 subtyping and expression of additional genes was performed on 63 patients with HR+/HER2− disease randomly assigned to neoadjuvant multiagent chemotherapy versus endocrine therapy in a phase II trial. The biology associated with treatment response was used to derive a PAM50-based chemoendocrine score (CES). CES's predictive ability was evaluated in 4 independent neoadjuvant data sets (n = 675) and 4 adjuvant data sets (n = 1,505). The association of CES, intrinsic biology, and PAM50 risk of relapse (ROR) was explored across 6,007 tumors. Results: Most genes associated with endocrine sensitivity were also found associated with chemotherapy resistance. In the chemotherapy test/validation data sets, CES was independently associated with pathologic complete response (pCR), even after adjusting for intrinsic subtype. pCR rates of the CES endocrine–sensitive (CES-E), uncertain (CES-U), and chemotherapy-sensitive (CES-C) groups in both data sets combined were 25%, 11%, and 2%, respectively. In the endocrine test/validation data sets, CES was independently associated with response. Compared with ROR, >90% of ROR-low and ROR-high tumors were identified as CES-E and CES-C, respectively; however, each CES group represented >25% of ROR-intermediate disease. In terms of survival outcome, CES-C was associated with poor relapse-free survival in patients with ROR-intermediate disease treated with either adjuvant endocrine therapy only or no adjuvant systemic therapy, but not in patients treated with (neo)adjuvant chemotherapy. Conclusions: CES is a genomic signature capable of estimating chemoendocrine sensitivity in HR+ breast cancer beyond intrinsic subtype and risk of relapse. Clin Cancer Res; 23(12); 3035–44. ©2016 AACR.

Germ cell tumors (GCTs) are a heterogeneous group of tumors that are highly clinically relevant to oncologists. GCTs are generally highly sensitive to cisplatin-based chemotherapy and represent a model for curable neoplasms. Cisplatin-based combination therapy followed by surgical resection of the residual tumor is the cornerstone for GCTs treatment. Although the overall cure rate is high for patients with GCTs, patients with a poor prognosis according to International Consensus Criteria or with chemoresistant disease remain a major clinical challenge. Currently, between 15% and 20% of patients with metastatic disease still progress and will die as a consequence of the disease. Therefore, the discovery of new treatment strategies or new drugs based on translational oncology remains a priority for the treatment of patients with cisplatin-refractory disease and those with a poor prognosis. Clinical trials with new targeted therapies are ongoing for the treatment of GCTs. In this article, we review some of the new targeted biologic therapies that act on the most relevant oncogenesis pathways and are in clinical development for the treatment of GCTs.

The prognosis and need or not for adjuvant therapy in patients with small breast tumors (≤1cm N0) is the subject of controversy as regards the clinical benefit obtained, toxicity, and the economical costs generated. A retrospective analysis was made of 238 patients with early-stage breast cancer (pT1≤1 cm N0M0) diagnosed between January 1993 and May 2008. As regards the systemic adjuvant treatments provided, (a) 122 (51%) received no treatment, (b) 102 (43%) received hormone therapy, (c) 9 (4%) chemotherapy, and (d) 5 (2%) received both hormone therapy and chemotherapy. An analysis was made of disease-free survival (DFS) and breast cancer-specific survival in our series of patients, and of their correlation to clinicopathological factors (age, tumor size, histological grade, estrogen receptor (ER) expression, HER-2 overexpression, and systemic adjuvant therapy). The median follow-up of this cohort was 63months (range 5-145). Some type of relapse was recorded in 4.2% of the patients (six patients presented local recurrence in all cases subjected to rescue treatment with surgery and/or radiotherapy, three patients developed distant metastases, and one patient presented a resected local recurrence followed by systemic relapse). The 5year DFS was 96%, and the 5year breast cancer-specific survival was 99.6%. A univariate analysis was made of the clinicopathological variables and their association to DFS. None of the variables was seen to be significantly correlated to shorter DSF except for an association between HER-2 overexpression and poor outcome borderline significance (p=0.07). The prognosis of our pT1≤1cm N0M0 tumors was excellent, although the absence of systemic adjuvant therapy in one-half of the patients.

Breast cancer is a heterogeneous disease characterised by a dysregulation of multiple pathways related to cell differentiation, cell cycle control, apoptosis, angiogenesis and development of metastasis. Acting against these pathways provides therapeutic targets for new targeted biologic therapies, which, in the future, might constitute a key for fighting cancer. The development of molecular technology in recent years has allowed a further comprehension of these mutations and dysregulated pathways leading to oncogenesis. New targeted biologic therapies will block essential functions of cancer cells and tumour stroma. A growing number of therapy options, alone or in combination with background treatments (chemotherapy, hormone therapy, radiotherapy), will allow oncologists a better adaptation of treatment to patients and disease characteristics. Examples of approved targeted agents in breast cancer include agents targeting the human epidermal growth factor receptor 2 (HER2), such as trastuzumab, lapatinib and the anti-VEGF bevacizumab. In addition, there are other therapy classes under evaluation, including novel antiEGFR or antiHER2 therapies; agents fighting other tyrosine kinases, including the Src and the insulin-like growth factor receptor; agents interfering critically relevant pathways, such as PI3K/AKT/mTOR inhibitors; and agents promoting apoptosis, such as PARP inhibitors (for particular breast cancer subtypes, such as basal-like, or breast cancer with BRCA mutations) and others. The better selectivity against malignant cells of these therapies, when compared to conventional chemotherapy, gives, a priori, at least two advantages to biologic treatments: fewer side effects and a more individualised treatment of cancer depending on the tumour’s molecular characteristics. The ability to identify patients’ subgroups and response predicting factors will be crucial in obtaining the greatest benefit with minimal toxicity levels. Unsolved questions remain, such as appropriate patient selection based on the expression of the therapeutic target in the tumour, the study of the efficacy of the drug in not so extensively pretreated populations and with a greater chance of response, the use of new pharmacodynamic models to help to define new response predicting factors for a specific new biologic therapy, the combined and rational use of different biologic therapies having different molecular targets and fighting the same target through a complementary mechanism of action that might improve clinical efficacy.

Tolerability of molecularly targeted agents (MTA) used in cancer therapeutics is determined in phase I trials. We reviewed the reported incidence of toxicity in phase III trials at doses and schedules recommended by phase I trials to evaluate whether these recommendations are realistic when drugs are used in larger populations of patients. We systematically reviewed a safety profile of small molecule (SM-MTA) and mAb MTA (MA-MTA) approved by the FDA in the last 12 years. There was a significantly increased percentage of grade 3 or 4 adverse events reported with SM-MTA compared with MA-MTA [40% vs. 27%; RR 1.5; 95% confidence interval (CI), 1.10-2.25, P = 0.038] in phase III studies. Importantly, a substantial proportion of patients (45%) treated with SM-MTA required dose modifications due to drug-related toxicity in phase III trials. However, this toxicity was associated to a definitive study drug discontinuation in only 9%. Overall, 25% of SM-MTA declared recommended phase II doses below MTD based on pharmacokinetic-pharmacodynamic data and these trials were associated with a significantly reduced number of dose modifications in registration trials (32% vs. 50%; RR 0.64; 95% CI, 0.43-0.88, P = 0.01). Tolerability is going to come into further focus due to the need for combinations of SM-MTA and other anticancer agents. There was a higher incidence of grade 3-4 toxicity in phase III trials in combinations versus single-agent SM-MTAs (64% vs. 37%; RR 1.73; 95% CI, 1.3-2.3, P = 0.001). These results indicate that phase I studies underestimate toxicity while recommending doses of SM-MTA. Clin Cancer Res; 22(9); 2127-32. ©2015 AACR.

Background: Gene expression profiling and their immunohistochemistry-based surrogates have consistently revealed prognostically significant breast cancer (BC) subtypes: Luminal A (Lum A), Luminal B (Lum B), HER2, Basal-like (BL) and Triple negative phenotype-nonbasal (TNP-nb). In addition, there are clinical evidence that hazard of BC recurrence varies over time with two peaks of high risk at 18–24 and 60 months. This study compares the time-related patterns of recurrence within BC subtypes. Methods: Tissue microarrays were constructed from 937 early BC patients diagnosed and treated at our Hospital from 1982 to 2005 with available archival paraffin tissue blocks. BC subtypes were defined using an immunopanel of estrogen receptor, progesterone receptor, HER2, epidermal growth factor receptor, cytokeratin 5/6 and Ki67 by prespecified published methods. Univariate and multivariate analysis (Cox regression) were performed on progression-free survival. Smoothed curves for hazard rates (HR) were estimated by a Kernel-like smoothing procedure. The statistical analysis was done by using the R software environment. Results: Cases were classified as follows: Lum A 46.8%, Lum B 25.2%, HER2 11.3%, BL 11.3%, TNP-nb 5.4%. None of the patients were treated with adjuvant trastuzumab. With a median follow up of 80 months age, tumor size, nodal status and intrinsic subtypes were independent prognostic factors. HER2 and BL show high and early peak in HR curves and decreasing sharply to 36 and 48 months respectively. HR in Lum A, Lum B and TNP-nb exhibit a smoother and nearly steady curve. Conclusions: BC subtypes have distinct outcome but also displays different pattern of recurrence over time. These data might imply that pathways underlying early and late recurrences could be different. This additional information would suggest the convenience of considering different timings and duration of adjuvant treatments depending of BC subtypes, and also in the design of surveillance recommendations. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P3-05-04.

Blubber and liver samples from six striped dolphins (Stenella coeruleoalba) found dead in the Mediterranean Sea in 1989--1990 were tested for 37 coplanar and chiral polychlorinated biphenyls (PCBs), including the enantiomeric ratios of 9 chiral PCBs. The method includes a fractionation step using HPLC (PYE column) for separating the PCBs according to the number of chlorine atoms in the ortho positions. HRGC/ECD and HRGC/LRMS with an a chiral column (DB-5) were used to determine the PCB congeners. The enantiomeric ratios of nine chiral PCBs were determined by HRGC/LRMS (SIM) with a chiral column (Chirasil-Dex) and by MDGC as the confirmatory technique. The total PCB concentration (sum of 37 congeners) ranged from 7.2 to 89.6 {micro}g/g (wet weight) and from 0.52 to 29.2 {micro}g/g (wet weight) for blubber and liver samples, respectively. PCB profiles were dominated by congeners 138, 153, 170, and 180. The toxic equivalent values (TEQ) ranged from 0.17 to 3.93 ng/g (wet weight) and from 0.02 to 0.73 ng/g (wet weight) for blubber and liver samples, respectively. PCBs 95, 132, 135, 149, and 176 revealed an enantiomeric excess of the second eluted enantiomer in almost all of the samples, whereas PCBs 136 and 174 were racemic or almostmore » racemic. PCBs 88 and 91 were under the detection limits of the methodology used.« less

5594 Background: The addition of cetuximab to weekly paclitaxel have shown high efficacy in the first-line treatment of patients with recurrent /metastatic squamous cell carcinoma of the head and n...

e21047 Background: Gene expression profiling and their immunohistochemistry-based surrogates have consistently revealed prognostically significant breast cancer (BC) subtypes: Luminal A (Lum A), Lu...

5528 Background: HPV-related HNSCC has been associated with an improved prognosis in patients treated with RT +/- CT; however, no information is available regarding patients treated with RT + EGFR ...