Does "One Size Fits All"? Rethinking FIGO Depth of Invasion Measurements in Vulvar Cancer

Depth of invasion (DOI) is an important diagnostic parameter in patients with vulvar carcinoma, where a cutoff value of 1 mm largely determines the tumor stage and the need for groin surgery. DOI measurement should be reproducible and straightforward. In light of the new recommendation on how to measure DOI in the International Federation of Gynecology and Obstetrics (FIGO) staging system 2021, an exploratory study was conducted on the current practice of DOI measurement in vulvar cancer. In this study of 26 selected cases, 10 pathologists with high exposure to vulvar cancer cases in daily practice assessed both the conventional (FIGO 2009) and alternative (FIGO 2021) DOI methods for applicability and preference. In this set of cases, the DOI measurement according to FIGO 2009 was generally considered easier to apply than the measurement according to FIGO 2021, with applicability being rated as "easy to reasonable" in 76.9% versus 38.5% of cases, respectively (P=0.005). The preferred method was FIGO 2009 or tumor thickness in 14 cases and FIGO 2021 in 6 cases. No invasion was preferred in 1 case. For the remaining 5 cases, half of the pathologists opted for the FIGO 2009 method and half for the FIGO 2021 method. Although the FIGO 2009 method proved to be more readily applicable in most of the cases studied, the method may differ for each case. There may not be a "one size fits all" solution for all cases of vulvar cancer.

The prognostic value of tumor-stroma ratio and a newly developed computer-aided quantitative analysis of routine H&E slides in high-grade serous ovarian cancer

INTRODUCTION

Tumor-stroma ratio (TSR) is prognostic in multiple cancers, while its role in high-grade serous ovarian cancer (HGSOC) remains unclear. Despite the prognostic insight gained from genetic profiles and tumor-infiltrating lymphocytes (TILs), the prognostic use of histology slides remains limited, while it enables the identification of tumor characteristics via computational pathology reducing scoring time and costs. To address this, this study aimed to assess TSR's prognostic role in HGSOC and its association with TILs. We additionally developed an algorithm, Ovarian-TSR (OTSR), using deep learning for TSR scoring, comparing it to manual scoring. Methods : 340 patients with advanced-stage who underwent primary debulking surgery (PDS) or neo-adjuvant chemotherapy (NACT) with interval debulking (IDS). TSR was assessed in both the most invasive (MI) and whole tumor (WT) regions through manual scoring by pathologists and quantification using OTSR. Patients were categorized as stroma-rich (≥ 50% stroma) or stroma-poor (< 50%). TILs were evaluated via immunohistochemical staining. Result s: In PDS, stroma-rich tumors were significantly associated with a more frequent papillary growth pattern (60% vs 34%), while In NACT stroma-rich tumors had a lower Tumor Regression Grading (TRG 4&5, 21% vs 57%) and increased pleural metastasis (25% vs 16%). Stroma-rich patients had significantly shorter overall and progression-free survival compared to stroma-poor (31 versus 45 months; P < 0.0001, and 15 versus 17 months; P = 0.0008, respectively). Combining stromal percentage and TILs led to three distinct survival groups with good (stroma-poor, high TIL), medium (stroma-rich, high TIL, or; stroma-poor, Low TIL), and poor(stroma-rich, low TIL) survival. These survival groups remained significant in CD8 and CD103 in multivariable analysis (Hazard ratio (HR) = 1.42, 95% Confidence-interval (CI) = 1.02-1.99; HR = 1.49, 95% CI = 1.01-2.18, and HR = 1.48, 95% CI = 1.05-2.08; HR = 2.24, 95% CI = 1.55-3.23, respectively). OTSR was able to recapitulate these results and demonstrated high concordance with expert pathologists (correlation = 0.83). Conclusions : TSR is an independent prognostic factor for survival assessment in HGSOC. Stroma-rich tumors have a worse prognosis and, in the case of NACT, a higher likelihood of pleural metastasis. OTSR provides a cost and time-efficient way of determining TSR with high reproducibility and reduced inter-observer variability.

Abstract P3-06-01: Unleashing NK- and CD8 T cells by combining monalizumab (anti-NKG2A) and trastuzumab for metastatic HER2+ breast cancer: first results MIMOSA trial

Background Although treatment options and survival of HER2+ metastatic breast cancer (MBC) patients have greatly improved, the majority of MBC-patients still die of this disease. The relatively high levels of TILs observed in this BC subtype provide a rationale for immunomodulatory strategies, however, PD1-blockade has only shown modest response rates in this setting. While PD-1 blockade mainly acts on T cells, monalizumab targets the inhibitory immune checkpoint NKG2A which interacts with HLA-E on tumor cells, thereby unleashing NK- as well as CD8 T cells. We hypothesize that monalizumab can promote antibody-dependent cell-mediated cytotoxicity (ADCC) which is critical for trastuzumab efficacy. Clinical activity was shown in patients with head and neck cancer when monalizumab was combined with cetuximab (anti-EGFR). Here, we present the first results of the MIMOSA-trial investigating the efficacy of the novel combination monalizumab and trastuzumab in patients with HER2+ MBC. Methods In the phase II MIMOSA-trial (NTC04307329), HER2+ MBC patients were treated biweekly with 4mg/kg trastuzumab and 750mg monalizumab. Key eligibility criteria were progressive disease despite anti-HER2 therapy, had received a minimum of one and a maximum of three lines of palliative chemotherapy, had measurable disease according to RECIST1.1, and a serum LDH-level below 500U/L. Primary endpoint was objective response rate according to RECIST1.1. Secondary endpoints included clinical benefit rate (complete response CR, partial response PR or stable disease SD for at least 6 months) according to RECIST1.1, progression-free survival, overall survival and safety. Dose-limiting toxicities were continuously monitored throughout the trial and evaluated using a pre-defined Pocock-type boundary rule. Following a Simon’s two-stage design, 11 patients were included in stage I of the trial. If two or more responders were observed, further exploration is warranted in stage II. Results Between January 2021 and April 2022, eleven women of which ten are currently evaluable were enrolled in the trial. Patients received a median of two lines of prior treatment for MBC, of which 6 out of 11 patients were treated with trastuzumab emtansine (T-DM1). The majority of patients had hormone receptor positive BC (72% of the patients) and had low levels of tumor-infiltrating lymphocytes (TILs) with a median of 1% (ranging from 1% to 20%). Patients received a median of four cycles of trastuzumab and monalizumab. Treatment was well tolerated with no dose-limiting toxicities. No objective responses were observed in the first ten out of eleven evaluable patients. Therefore, MIMOSA stage I did not meet its primary endpoint, leading to discontinuation of the trial. Conclusions The novel combination of trastuzumab and monalizumab did not induce objective responses in heavily pre-treated HER2+ MBC patients.

Citation Format: Veerle Geurts, Leonie Voorwerk, Karolina Sikorska, Roberto Salgado, Koen van de Vijver, Marloes van Dongen, Inge Kemper, Ingrid A. Mandjes, Martine Heuver-mes, John Haanen, Gabe S. Sonke, Hugo Horlings, Marleen Kok. Unleashing NK- and CD8 T cells by combining monalizumab (anti-NKG2A) and trastuzumab for metastatic HER2+ breast cancer: first results MIMOSA trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-06-01.

External Quality Assessment 2.0: The Importance of a Standardized Implementation of TILs for Daily and Trial Practices

New assays are developed regularly to improve health care for patients. It is important to ensure that assays are performed correctly. Therefore, it is advised to participate in training and proficiency (competence assessment) programs. Tumor infiltrating lymphocytes (TILs) might improve the estimates of response to therapy and prognosis. Herewith, we propose a new training and proficiency program in which each pathologist can train and test themselves regarding TILs (and PDL1) scoring.

Abstract PD11-03: Deep learning applied on resection specimen tissue slides of ‘pure’ ductal carcinoma in situ predicts ipsilateral invasive breast cancer recurrence

Clinical problem. Ductal Carcinoma in Situ (DCIS) is a potential precursor for invasive breast cancer (IBC). Therefore, DCIS is currently treated with surgical excision, often supplemented with radiotherapy to prevent progression to ipsilateral IBC (iIBC). However, many DCIS lesions will never do so. Estimating the risk of progression is a grand challenge, as neither the histopathological grade of the DCIS lesion nor other biological markers are conclusively associated with the disease outcome. Aim. We aimed to develop a deep-learning based pipeline for estimating the risk of iIBC recurrence following DCIS using a dataset of 235 H&E-stained whole-slide images (WSIs) of the primary DCIS lesions with corresponding 10-year follow up metadata of DCIS recurrence collected at the Netherlands Cancer Institute. The patients included in our dataset did not receive radiotherapy and experienced recurrence in 167 of the cases. Results. We developed a two-step pipeline that is able to find predictive features for 10-year iIBC prediction. First, tissue regions on WSIs were divided into equally sized tiles. Mammary ducts were detected in the tiles using a RetinaNet with ResNet101 backbone that was implemented in Detectron2 and pre-trained on ImageNet. Selecting only tiles containing ducts served to reduce the input dimensionality of typically giga-pixel WSIs for the second step. Here, DCIS recurrence was predicted by a weakly-supervised multi-instance learning (MIL) classification model where the label of the WSI was determined by average weighting of duct labels. The performance of this model was enhanced by pre-training it with SimCLR, a self-supervised learning method, on image data from the histopathology domain. Our proposed model achieved an AUC of .93 ± .005, with a sensitivity of .83 ± .27 and a specificity of .85± .09. These results show that the model was able to correctly distinguish patients with low subsequent IBC-risk from those with a substantially higher risk. An active research pursuit of our group is now to develop a model which is able to predict iIBC progression for patients treated with radiotherapy. This poses additional challenges to the model, as the effect of radiotherapy, as well as disease outcome must be predicted. Conclusion and impact. Our method opens up an avenue for identifying biologically relevant features for estimating DCIS progression risk into invasive breast cancer. This knowledge may be used for appropriately choosing a personalized DCIS management option for patients - which may be active surveillance rather than surgical removal of the lesion. JW and JT were equal senior co-authors on this project. This work was supported by Cancer Research UK and by KWF Dutch Cancer Society (ref.C38317/A24043)

Citation Format: Shannon Doyle, Francesco Dal Canton, Timo Koostra, Maartje van Seijen, Emilie Groen, Efstratios Gavves, Hugo Horlings, Esther Lips, Jelle Wesseling, Jonas Teuwen, Grand Challenge PRECISION Consortium. Deep learning applied on resection specimen tissue slides of ‘pure’ ductal carcinoma in situ predicts ipsilateral invasive breast cancer recurrence [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr PD11-03.

The tale of TILs in breast cancer: A report from The International Immuno-Oncology Biomarker Working Group

The advent of immune-checkpoint inhibitors (ICI) in modern oncology has significantly improved survival in several cancer settings. A subgroup of women with breast cancer (BC) has immunogenic infiltration of lymphocytes with expression of programmed death-ligand 1 (PD-L1). These patients may potentially benefit from ICI targeting the programmed death 1 (PD-1)/PD-L1 signaling axis. The use of tumor-infiltrating lymphocytes (TILs) as predictive and prognostic biomarkers has been under intense examination. Emerging data suggest that TILs are associated with response to both cytotoxic treatments and immunotherapy, particularly for patients with triple-negative BC. In this review from The International Immuno-Oncology Biomarker Working Group, we discuss (a) the biological understanding of TILs, (b) their analytical and clinical validity and efforts toward the clinical utility in BC, and (c) the current status of PD-L1 and TIL testing across different continents, including experiences from low-to-middle-income countries, incorporating also the view of a patient advocate. This information will help set the stage for future approaches to optimize the understanding and clinical utilization of TIL analysis in patients with BC.

Interobserver Agreement of PD-L1/SP142 Immunohistochemistry and Tumor-Infiltrating Lymphocytes (TILs) in Distant Metastases of Triple-Negative Breast Cancer: A Proof-of-Concept Study. A Report on Behalf of the International Immuno-Oncology Biomarker Working Group

Patients with advanced triple-negative breast cancer (TNBC) benefit from treatment with atezolizumab, provided that the tumor contains ≥1% of PD-L1/SP142-positive immune cells. Numbers of tumor-infiltrating lymphocytes (TILs) vary strongly according to the anatomic localization of TNBC metastases. We investigated inter-pathologist agreement in the assessment of PD-L1/SP142 immunohistochemistry and TILs. Ten pathologists evaluated PD-L1/SP142 expression in a proficiency test comprising 28 primary TNBCs, as well as PD-L1/SP142 expression and levels of TILs in 49 distant TNBC metastases with various localizations. Interobserver agreement for PD-L1 status (positive vs. negative) was high in the proficiency test: the corresponding scores as percentages showed good agreement with the consensus diagnosis. In TNBC metastases, there was substantial variability in PD-L1 status at the individual patient level. For one in five patients, the chance of treatment was essentially random, with half of the pathologists designating them as positive and half negative. Assessment of PD-L1/SP142 and TILs as percentages in TNBC metastases showed poor and moderate agreement, respectively. Additional training for metastatic TNBC is required to enhance interobserver agreement. Such training, focusing on metastatic specimens, seems worthwhile, since the same pathologists obtained high percentages of concordance (ranging from 93% to 100%) on the PD-L1 status of primary TNBCs.

Spatial immunophenotypes predict response to anti-PD1 treatment and capture distinct paths of T cell evasion in triple negative breast cancer

Only a subgroup of triple-negative breast cancer (TNBC) responds to immune checkpoint inhibitors (ICI). To better understand lack of response to ICI, we analyze 681 TNBCs for spatial immune cell contextures in relation to clinical outcomes and pathways of T cell evasion. Excluded, ignored and inflamed phenotypes can be captured by a gene classifier that predicts prognosis of various cancers as well as anti-PD1 response of metastatic TNBC patients in a phase II trial. The excluded phenotype, which is associated with resistance to anti-PD1, demonstrates deposits of collagen-10, enhanced glycolysis, and activation of TGFβ/VEGF pathways; the ignored phenotype, also associated with resistance to anti-PD1, shows either high density of CD163+ myeloid cells or activation of WNT/PPARγ pathways; whereas the inflamed phenotype, which is associated with response to anti-PD1, revealed necrosis, high density of CLEC9A+ dendritic cells, high TCR clonality independent of neo-antigens, and enhanced expression of T cell co-inhibitory receptors.

Abstract A75: Serine auxotrophy: A novel metabolic vulnerability of platinum-resistant ovarian cancer?

Ovarian cancer accounts for the highest number of gynecologic-associated deaths in the developed world, and resistance to platinum-based therapy represents a major clinical and societal challenge in patients’ management. Since metabolism is intertwined with signaling pathways controlling cell death, we aimed to investigate to what extent metabolic adaptations could contribute to the development of the resistant phenotype. By performing isotope-labeled 13C-glucose tracer analysis in vitro, we found that, when they become resistant to platinum, ovarian cancer cells stop to synthetize serine and are characterized by significantly lower intracellular levels of this amino acid compared to sensitive cells. However, serine is required for cellular growth and survival, and resistant cells increase its uptake from the medium, becoming exquisitely vulnerable to serine starvation. We showed that, although resistant cells accumulate DNA damage upon platinum treatment, they have a higher capacity of repairing it because of increased poly(ADP)-ribose polymerase (PARP) activity, compared to the sensitive ones. Since PARP enzymes are major oxidized nicotinamide adenine dinucleotide (NAD+)-consuming enzymes, we collected evidence that serine synthesis downregulation, as a consequence of central carbon metabolic reshuffling, provides resistant cells with the advantage of sparing NAD+, thus sustaining PARP activation and allowing a more efficient DNA repair. We confirmed that downregulation of serine synthesis is a peculiar trait of resistant tumors also in vivo, using patient-derived xenografts (PDX) ovarian cancer models subjected to serine/glycine free diet. Moreover, analysis of The Cancer Genome Atlas Consortium (TCGA) ovarian cancer dataset revealed that tumors from platinum-resistant patients are characterized by a downregulation of serine biosynthetic enzymes, suggesting that serine auxotrophy could represent a novel and exploitable vulnerability of platinum-resistant ovarian cancers.

Citation Format: Tom Van Nyen, Joao A.G. Duarte, Matteo Rossi, Mélanie Planque, Esther Zaal, Ali Talebi, Stijn Moens, Guy Eelen, Hugo Horlings, Johan Swinnen, Celia Berkers, Peter Carmeliet, Reuven Agami, Sarah-Maria Fendt, Diether Lambrechts, Daniela Annibali, Frederic Amant. Serine auxotrophy: A novel metabolic vulnerability of platinum-resistant ovarian cancer? [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research; 2019 Sep 13-16, 2019; Atlanta, GA. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(13_Suppl):Abstract nr A75.

Spatial proximity of CD8 T cells to tumor cells as an independent biomarker for response to anti-PD-1 therapy

10038

Background: Only a subset of advanced melanoma patients respond to anti-PD-1 (aPD1) monotherapy. Upfront identification of (non-)responsiveness would help guide first-line treatment decisions, prevent overtreatment and unnecessary risk for toxicities. T cell density and expression of T cell related genes have been associated with response to aPD1, but are imperfect predictors. We investigated whether spatial proximity of CD8 T cells to tumor cells improves upon the predictive value of T cell density alone. Methods: Pretreatment tumor specimens from melanoma patients treated with aPD1 in the Netherlands Cancer Institute were stained for DAPI, SOX10/Melan-A, CD4, CD8, FOXP3 and PD-1 by multiplex immunofluorescence. Sections were imaged on Vectra and analyzed using HALO to optimize marker thresholds and demarcate tumor and stroma. T cell proximity to tumor cells was evaluated as difference in area under the curve between i) a spatial G-function quantifying T cell density around tumor cells in tumor areas and ii) analogous null distributions obtained by random permutation of cell labels. This assessment of co-clustering is independent of cell density and heterogeneity therein and does not reflect repulsion of T cells to stromal/marginal areas. Clinical characteristics, RECIST response and survival were collected from patient records. Associations between T cell density, T cell proximity to Sox10/Melan-A+ tumor cells, other clinical biomarkers (LDH, M stage and WHO performance status) and response were examined in a Bayesian hierarchical logistic regression. Results: Tumor specimens of 98 patients were included, of whom 45 were treated with aPD1 as first-line therapy and 33 had an objective response. CD8 T cell proximity to tumor cells was associated with response in an independent, comparatively strong, and tissue dependent manner (cutaneous tissue: 2.78 [2.45, 3.17], visceral: 2.30 [1.95, 2.72], lymphoid: 2.12 [1.88, 2.40], format: maximal posteriori odds ratio [89% equal-tailed credibility interval]), in a multivariate model correcting for CD8 T cell density (1.74 [1.62, 1.88]), LDH (1.93 [1.72, 2.16]), M stage (0.92 [0.87, 0.98]) and WHO performance status (0.79 [0.72, 0.88]). Our model achieved an area under the ROC curve of 77.7%, whereas an analogous model omitting the proximity variable achieved 73.1%. Conclusions: Our analyses show that spatial proximity of CD8 T cells to tumor cells functions as an independent biomarker for response to aPD1 and suggests that preexisting CD8 T cell tumor reactivity is reflected by this spatial proximity.

Characteristics and Outcome of AKT1 E17K-Mutant Breast Cancer Defined through AACR Project GENIE, a Clinicogenomic Registry

AKT inhibitors have promising activity in AKT1 ^E17K-mutant estrogen receptor (ER)-positive metastatic breast cancer, but the natural history of this rare genomic subtype remains unknown. Utilizing AACR Project GENIE, an international clinicogenomic data-sharing consortium, we conducted a comparative analysis of clinical outcomes of patients with matched AKT1 ^E17K-mutant (n = 153) and AKT1-wild-type (n = 302) metastatic breast cancer. AKT1-mutant cases had similar adjusted overall survival (OS) compared with AKT1-wild-type controls (median OS, 24.1 vs. 29.9, respectively; P = 0.98). AKT1-mutant cases enjoyed longer durations on mTOR inhibitor therapy, an observation previously unrecognized in pivotal clinical trials due to the rarity of this alteration. Other baseline clinicopathologic features, as well as durations on other classes of therapy, were broadly similar. In summary, we demonstrate the feasibility of using a novel and publicly accessible clincogenomic registry to define outcomes in a rare genomically defined cancer subtype, an approach with broad applicability to precision oncology. SIGNIFICANCE: We delineate the natural history of a rare genomically distinct cancer, AKT1 ^E17K-mutant ER-positive breast cancer, using a publicly accessible registry of real-world patient data, thereby illustrating the potential to inform drug registration through synthetic control data.See related commentary by Castellanos and Baxi, p. 490.

Abstract LB-103: Landscape of somatic ERBB2 Mutations: Findings from AACR GENIE and comparison to ongoing ERBB2 mutant basket study

Background: AACR GENIE is an international data-sharing project that aggregates clinical-grade cancer genomic data. As a demonstration of utility, we evaluated the landscape of ERBB2 mutations in the first 18,486 patients included in this registry and compared it to the first 100 patients enrolled in an ongoing international Phase 2 SUMMIT ‘basket’ study of the pan-HER inhibitor neratinib in ERBB2 mutant solid tumors (NCT01953926). Results: ERBB2 mutations were identified in 2.8% (519/18,486) of patients in the GENIE cohort and observed at all participating centers. In total, there were 482 missense, 66 indels, 19 truncating mutations, and 14 structural variants. A total of 263 unique missense mutations were observed including 12 at previously identified hotspots which accounted for 69.2% of all missense mutations. 35 unique cancer types were represented. The tumor types with the highest proportion of ERBB2 mutations were bladder (12.8%, 82/641), breast (3.9%, 87/2230), colorectal (3.3%, 70/2102), and NSCLC (3%, 90/3006). Among patients with copy number data available (91%) 11% had concurrent ERBB2 amplification, most often in breast cancer. The most frequently observed alterations in ERBB2, adjusted for differing exon coverage between panels, was S310F/Y in 0.46% of the GENIE cohort (12.6% of samples with ERBB2 alterations), Y772_A775dup in 0.21% (6.9%), R678Q in 0.17% (4.5%), L755S in 0.16% (5.2%), V777L in 0.12% (3.8%), and V842I in 0.09% (3.1%). The distribution of specific ERBB2 variants differed significantly by tumor type with exon 20 insertions being most common in NSCLC (44.4%, 40/90), L755S (18.9%, 11/92) in breast, S310F/Y (26.9%, 28/104) in bladder, and V842I (13.9%, 10/72) in colorectal cancer. Structural variants included intragenic deletions (n=4) and fusions involving various partners including GRB7 (n=2), and one each of C1orf87, PPIL6, HEXIM2, THRA, ASIC2, BCA3, WIPF2. The frequencies of ERBB2 mutant cancer types observed in the GENIE cohort were generally comparable to those enrolled to the neratinib basket study including NSCLC (17 vs 22%, respectively), breast (16.4 vs 24%), bladder (15.5 vs 14%), colorectal (13.2 vs 17%), and endometrial (4.2 vs 6%). At the variant level, S310F/Y was less prevalent in GENIE compared to the neratinib study (12.6 vs 24%) while all other mutations were generally similar including L755S (5.2 vs 9%), R678Q (4.5 vs 2%), Y772_A775dup (6.9 vs 13%), V777L (3.8 vs 9%), and V842I (3.1 vs 6%). Conclusion: GENIE confirms that a diversity of ERBB2 mutations are prevalent across a variety of tumor types in patients with advanced cancer. The genomic landscape of ERBB2 mutations was largely similar in the population based GENIE cohort and the neratinib SUMMIT study, providing the first direct evidence that basket study enrollment accurately reflects the true landscape of the target alteration.

Citation Format: Alison Schram, Helen H. Won, Fabrice Andre, Monica Arnedos, Funda Meric - Bernstam, Philippe L. Bedard, Kenna R. Shaw, Hugo Horlings, Christine Micheel, Ben Ho Park, Grace Mann, Alshad S. Lalani, Lillian Smyth, David B. Solit, Deborah Schrag, Mia A. Levy, Barrett J. Rollins, Mark Routbort, Charles L. Sawyers, Eva Lepisto, Michael F. Berger, David M. Hyman, on behalf of the AACR Project GENIE Consortium. Landscape of somatic ERBB2 Mutations: Findings from AACR GENIE and comparison to ongoing ERBB2 mutant basket study [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-103. doi:10.1158/1538-7445.AM2017-LB-103

Abstract 3697: SIRT2 is a modulator of response to targeted therapies through regulation of MEK kinase activity

Resistance to targeted therapies is a major problem in cancer treatment. The Epidermal Growth Factor Receptor (EGFR) antibody drugs are effective in a subset of colorectal cancers, but the molecular mechanisms of resistance are understood poorly. Genes involved in epigenetic regulation are frequently deregulated in cancer, raising the possibility that such genes also contribute to drug resistance. To address this question, we compiled an shRNA library for chromatin modifying enzymes, chromatin remodelers, and many other factors associated with chromatin regulation. Using this library, we performed a loss of function genetic screen in colon cancer cell lines sensitive to EGFR inhibitors. We identified SIRT2, a NAD+ dependent deacetylase, as a modulator of the response to EGFR inhibitors in colon and lung cancer. Mechanistically, loss of SIRT2 expression enhanced MEK acetylation, resulting in increased ERK activity. Conversely, overexpression of SIRT2 led to reduced phospho ERK and inhibition of growth. SIRT2 loss also conferred resistance to BRAF and MEK inhibitors in BRAF mutant melanoma and KRAS mutant colon cancers, respectively. These results warrant a further investigation into a potential role of SIRT2 in resistance to drugs that act in the Receptor Tyrosine Kinase-RAS-RAF-MEK-ERK signaling pathway.

Citation Format: Prashanth K. Bajpe, Anirudh Prahallad, Hugo Horlings, Iris Nagtegaal, Roderick Beijersbergen, Rene Bernards. SIRT2 is a modulator of response to targeted therapies through regulation of MEK kinase activity. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3697. doi:10.1158/1538-7445.AM2014-3697

Integrative molecular and functional profiling of ERBB2-amplified breast cancers identifies new genetic dependencies

Overexpression of the receptor tyrosine kinase ERBB2 (also known as HER2) occurs in around 15% of breast cancers and is driven by amplification of the ERBB2 gene. ERBB2 amplification is a marker of poor prognosis, and although anti-ERBB2-targeted therapies have shown significant clinical benefit, de novo and acquired resistance remains an important problem. Genomic profiling has demonstrated that ERBB2+ve breast cancers are distinguished from ER+ve and 'triple-negative' breast cancers by harbouring not only the ERBB2 amplification on 17q12, but also a number of co-amplified genes on 17q12 and amplification events on other chromosomes. Some of these genes may have important roles in influencing clinical outcome, and could represent genetic dependencies in ERBB2+ve cancers and therefore potential therapeutic targets. Here, we describe an integrated genomic, gene expression and functional analysis to determine whether the genes present within amplicons are critical for the survival of ERBB2+ve breast tumour cells. We show that only a fraction of the ERBB2-amplified breast tumour lines are truly addicted to the ERBB2 oncogene at the mRNA level and display a heterogeneous set of additional genetic dependencies. These include an addiction to the transcription factor gene TFAP2C when it is amplified and overexpressed, suggesting that TFAP2C represents a genetic dependency in some ERBB2+ve breast cancer cells.

ER Status and Immune Module Are Central Determinants of HER2 Amplified Infiltrative Breast Carcinoma Prognosis and Pathologic Complete Response

IntroductionGene expression profiling of invasive breast cancer has resulted in highlighting three main categories of breast cancer [luminal, basal, HER2] with very specific features. It has been shown that these subtypes differ in their response to neaoadjuvant systemic treatment, axillary lymph node involvement, metastasis pattern and time to metastasis. The aim of this study was to focus on gene-expression profile analysis of HER2 positive breast carcinoma to assess how the molecular subtype classification applies to the HER2+ve samples; whether subgroups of patients that have different prognosis can be identified and how subgroups can be identified that differ with respect to the likelihood to achieve pathologic complete response (pCR) after neoadjuvant systemic treatment?Materials and MethodWe selected breast carcinomas reported to have a HER2+ve status (IHC and CISH) from patients treated between January 1990 and December 2006 at the Netherlands Cancer Institute. 113 tumor samples were hybridized on the Human Genome Oligo Set Version 3.0 arrays. We identified 205 HER2+ve samples from 4 public microarrays datasets and 33 HER2+ve samples from one public neoadjuvant systemic treatment microarrays dataset.ResultsWe applied the molecular subtype classification to the whole datasets and found major classification instability. 43.3% of the HER2+ve samples were classified as “HER2 subtype”, 26% as “basal-like subtype”, and 21.9% as “luminal-like subtype”. The molecular subtype classification was not correlated to prognosis. Of the prognostic variables tested, only ER status was to the development of distant metastasis (IHC, HR=0.53 [0.36-0.77], p=0.0009). We identified a set of 109 ReporterID's highly enriched in gene ontology annotations link to the Immune Response and correlated to the prognosis of HER2+ve breast carcinoma (Inactivated Immune Module, HR=4.21 [1.94-9.17], logrank pvalue=8.1E-05). The Immune Module Signature was associated with prognosis of the HER2+ve samples in both ER positive and ER negative breast cancer. We validated this Immune Module signature combined with ER status on 205 independent samples.We applied the same classification tree to 33 samples from patients who were assessed for response to neo-adjuvant systemic chemotherapy (Anthracyclin-based) and showed an association between the Immune Module Signature combined with ER status and pCR rate (ER+ve Inactivated Immune Module 12.5% pCR, ER-ve Activated Immune Module 70% pCR, pvalue=0.1).ConclusionWe have shown that HER2+ve breast cancer samples often are not classified as HER2-like by gene expression profiling and that ER (IHC) status determines two major subgroups. We provide new evidence that an immune response relate gene expression classifier has prognostic impact in HER2+ve breast cancer; and that this classifier is potentially correlated to the pCR rate after neoadjuvant systemic treatment in HER2+ve breast cancer.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4037.

Integrative Molecular Profiling of Triple Negative Breast Cancers Identifies Potential Therapeutic Targets Including Amplifications of FGFR2

Triple negative breast cancers (TNBCs) have a relatively poor prognosis emphasising the need to identify new subtype specific target therapies. Based on the concept of oncogene addiction, we searched for potential therapeutic targets by identifying genes consistently over-expressed when amplified in TNBC. Fifty six TNBCs were subjected to high resolution tiling path microarray-based comparative genomic hybridisation (aCGH); out of these cases, 24 were also subjected to genome-wide microarray-based mRNA expression analysis. TNBCs showed a high level of genetic instability, with recurrent regions of amplification (&gt;4 copies) included multiple regions on 1q and 8q, 3q25, 10p14, 10q26, 13q34, 15q26 and 19q12-19q13. Integration of aCGH and expression data revealed 38 genes that were significantly overexpressed when amplified. This list includes known oncogenes and potential therapeutic targets, such as MCL1 (1q21.2), FGFR2 (10q26.3), BUB3 (10q26.3), RAB20 (13q34), PKN1 (19p13.12), and NOTCH3 (19p13.12). To validate FGFR2 as a therapeutic target, we screened a panel of cell lines, by western blotting and aCGH, and identified two TNBC cell lines with FGFR2 amplification. In these cell lines FGFR2 was constitutively active in a ligand independent manner, and RNA interference-mediated silencing of FGFR2 selectively decreased survival of cell lines harbouring FGFR2 amplification. Likewise FGFR2 amplified cell lines were highly sensitive to FGFR tyrosine kinase inhibitor PD173074 (IC50 &lt;20nM). Treatment with PD173074 induced apoptosis in amplified cell lines, as did treatment with PI3 kinase inhibitors LY294002 and BEZ-235 suggesting that apoptosis resulted from inhibition of AKT signalling. Examination of publically available CGH data sets confirmed FGFR2 amplification in 4% (5/124 95%CI 1.3-9.2%) of TNBC, with no cases of FGFR2 amplification in other subtypes (0/150, p=0.02). Our results suggest that FGFR2 amplification is a therapeutic target in a small subset of TNBCs.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 3147.

Different effects of insulin-like growth factor-1 receptor expression on prognosis of estrogen receptor positive versus triple-negative invasive ductal breast carcinoma

3546

Background: The insulin-like growth factor type 1 receptor (IGF-1R) is involved in progression and sensitivity to systemic treatment of breast cancer. Moreover, targeted inhibition of IGF-1R is likely to be beneficial in systemic treatment. However, it is unknown how to select patients for IGF-1R targeted therapy. Therefore, we studied the relation between IGF-1R expression and prognosis in invasive ductal breast carcinomas. Methods: Immunohistochemistry was performed on tumor tissue of a consecutive cohort of 429 female patients treated for operable primary invasive ductal breast carcinoma. TMA sections were stained with antibodies against IGF1-R, insulin receptor (IR), ER, PR, HER-2, epidermal growth factor receptor (EGFR) and phosphorylated-Akt (p-Akt). Cytoplasmic and membranous IGF-1R staining were scored separately, as the relevance of IGF-1R cellular localization is yet unknown. Associations between IGF-1R expression with clinical and tumor characteristics were evaluated in a multivariate Cox regression model. To study in more detail the prognostic role of IGF-1R expression in triple negative invasive ductal carcinomas (TN IDCs), 51 TN IDCs from the series described above were combined with 64 TN IDCs from an independent dataset with similar patient and clinico-pathological characteristics. Results: Patients with tumors expressing both ER and cytoplasmic IGF-1R have a longer disease free survival (HR = 0.20; 95% CI 0.07 - 0.63; p-value = 0.006) and breast cancer specific survival (HR = 0.20, 95% CI 0.07 - 0.63, p-value = 0.002), independent of other known prognostic factors. Conversely, in the combined series of 105 TN IDCs, cytoplasmic IGF-1R expression was associated with a shorter disease free survival (HR = 2.29; 95% CI 1.08 - 4.48, p-value = 0.03). In a multivariate model including known prognostic factors, cytoplasmic IGF-1R expression was nearly significantly related to a shorter disease free survival (HR 2.06; 95% CI 0.95 - 4.47; p = 0.07). Conclusions: The favorable versus unfavorable association with prognosis of IGF-1R expression in ER positive versus TN IDCs may provide new opportunities to select patients for IGF-1R targeted therapy.

No significant financial relationships to disclose.

Microarray-based determination of ER, PR and HER2 receptor status: validation and comparison with IHC assessments

Abstract #3007

Background&#x2028; In breast cancer patients the level of expression of estrogen receptor (ER), progesterone receptor (PR) and HER2 is predictive for prognosis and/or treatment response. However, differences in assessment methods and interpretation can substantially affect the accuracy and reproducibility of the results. Previously, we have determined the association between immunohistochemistry (IHC) and mRNA levels for ER, PR and HER2, and have confirmed the accuracy of microarray readout on &gt;400 samples. In the current study we describe the use of this microarray based readout on prospectively collected samples. We compared these readouts with multiple IHC and fluorescent in situ hybridization (FISH) assessments generated in various hospitals and a CLIA-certified reference laboratory and developed a microarray based test called TargetPrint™.&#x2028; Methods&#x2028; Gene expression data for ER, PR and HER2 were obtained by analysis of 100 breast carcinomas that have been collected prospectively within the RASTER study. Samples were stratified as receptor positive or negative using thresholds for ER, PR and HER2 mRNA levels. IHC assessment was performed (1) according to local standards of the hospital from where the sample originated, (2) by the central laboratory of the Netherlands Cancer Institute, and (3) at an independent reference laboratory using FDA-approved procedures and ASCO/CAP guidelines. A tumor was classified positive for ER and PR when ≥10% of tumor cells showed positive staining. HER2 IHC status was scored as 0, 1+, 2+ or 3+; a score of 3+ was considered positive. In case of 2+ samples, a FISH was performed to assess final HER2 amplification status. The cohort used in this study was pre-selected to include about two-third ER and PR positive samples and one-third HER2 positive samples.&#x2028; Results&#x2028; Multiple microarray readouts were highly reproducible (Pearson correlation 0.991) and resulted in 67, 61 and 39 percent positive samples for ER, PR and HER2, respectively. Comparison of microarray results with IHC (including FISH for HER2) performed at the three centers indicated highly similar results for receptor readout with a concordance of 92, 93 and 92% for ER; 84, 81 and 86% for PR; and 93, 95 and 94% for HER2. Overall misclassification rates between microarray and IHC readout were low for ER (0.08) and HER2 (0.06) and quite low for PR (0.14), and were comparable to the misclassification rates between the three IHC methods.&#x2028; Conclusion&#x2028; A microarray-based assessment of ER, PR and HER2 in relation to mRNA levels gives results comparable to multiple IHC methods and FISH and provides an objective and more quantitative assessment of tumor receptor status than IHC alone. Using TargetPrint™ for microarray readouts for hormone and HER2 receptor in addition to standard IHC will improve molecular characterization of breast cancer tissue.

Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 3007.

Robust prognostic value of a knowledge-based proliferation signature across large patient microarray studies spanning different cancer types

Tumour proliferation is one of the main biological phenotypes limiting cure in oncology. Extensive research is being performed to unravel the key players in this process. To exploit the potential of published gene expression data, creation of a signature for proliferation can provide valuable information on tumour status, prognosis and prediction. This will help individualising treatment and should result in better tumour control, and more rapid and cost-effective research and development. From in vitro published microarray studies, two proliferation signatures were compiled. The prognostic value of these signatures was tested in five large clinical microarray data sets. More than 1000 patients with breast, renal or lung cancer were included. One of the signatures (110 genes) had significant prognostic value in all data sets. Stratifying patients in groups resulted in a clear difference in survival (P-values <0.05). Multivariate Cox-regression analyses showed that this signature added substantial value to the clinical factors used for prognosis. Further patient stratification was compared to patient stratification with several well-known published signatures. Contingency tables and Cramer's V statistics indicated that these primarily identify the same patients as the proliferation signature does. The proliferation signature is a strong prognostic factor, with the potential to be converted into a predictive test. Furthermore, evidence is provided that supports the idea that many published signatures track the same biological processes and that proliferation is one of them.

An integrative genomic and proteomic analysis of PIK3CA, PTEN, and AKT mutations in breast cancer

Phosphatidylinositol 3-kinase (PI3K)/AKT pathway aberrations are common in cancer. By applying mass spectroscopy-based sequencing and reverse-phase protein arrays to 547 human breast cancers and 41 cell lines, we determined the subtype specificity and signaling effects of PIK3CA, AKT, and PTEN mutations and the effects of PIK3CA mutations on responsiveness to PI3K inhibition in vitro and on outcome after adjuvant tamoxifen. PIK3CA mutations were more common in hormone receptor-positive (34.5%) and HER2-positive (22.7%) than in basal-like tumors (8.3%). AKT1 (1.4%) and PTEN (2.3%) mutations were restricted to hormone receptor-positive cancers. Unlike AKT1 mutations that were absent from cell lines, PIK3CA (39%) and PTEN (20%) mutations were more common in cell lines than tumors, suggesting a selection for these but not AKT1 mutations during adaptation to culture. PIK3CA mutations did not have a significant effect on outcome after adjuvant tamoxifen therapy in 157 hormone receptor-positive breast cancer patients. PIK3CA mutations, in comparison with PTEN loss and AKT1 mutations, were associated with significantly less and inconsistent activation of AKT and of downstream PI3K/AKT signaling in tumors and cell lines. PTEN loss and PIK3CA mutation were frequently concordant, suggesting different contributions to pathophysiology. PTEN loss rendered cells significantly more sensitive to growth inhibition by the PI3K inhibitor LY294002 than did PIK3CA mutations. Thus, PI3K pathway aberrations likely play a distinct role in the pathogenesis of different breast cancer subtypes. The specific aberration present may have implications for the selection of PI3K-targeted therapies in hormone receptor-positive breast cancer.

Prediction of BRCA1-association in hereditary non-BRCA1/2 breast carcinomas with array-CGH

BACKGROUND

While new defects in BRCA1 are still being found, it is unclear whether current breast cancer diagnostics misses many BRCA1-associated cases. A reliable test that is able to indicate the involvement of BRCA1 deficiency in cancer genesis could support decision making in genetic counselling and clinical management. To find BRCA1-specific markers and explore the effectiveness of the current diagnostic strategy, we designed a classification method, validated it and examined whether we could find BRCA1-like breast tumours in a group of patients initially diagnosed as non-BRCA1/2 mutation carriers.

METHODS

A classifier was built based on array-CGH profiles of 18 BRCA1-related and 32 control breast tumours, and validated on independent sets of 16 BRCA1-related and 16 control breast carcinomas. Subsequently, we applied the classifier to 48 breast tumours of patients from Hereditary Breast and Ovarian Cancer (HBOC) families in whom no germ line BRCA1/BRCA2 mutations were identified.

RESULTS

The classifier showed an accuracy of 91% when applied to the validation sets. In 48 non-BRCA1/2 patients, only two breast tumours presented a BRCA1-like CGH profile. Additional evidence for BRCA1 dysfunction was found in one of these tumours.

CONCLUSION

We here describe the specific chromosomal aberrations in BRCA1-related breast carcinomas. We developed a predictive genetic test for BRCA1-association and show that BRCA1-related tumours can still be identified in HBOC families after routine DNA diagnostics.

Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas

INTRODUCTION

Breast cancer is a heterogeneous group of tumors, and can be subdivided on the basis of histopathological features, genetic alterations and gene-expression profiles. One well-defined subtype of breast cancer is characterized by a lack of HER2 gene amplification and estrogen and progesterone receptor expression ('triple-negative tumors'). We examined the histopathological and gene-expression profile of triple-negative tumors to define subgroups with specific characteristics, including risk of developing distant metastases.

METHODS

97 triple-negative tumors were selected from the fresh-frozen tissue bank of the Netherlands Cancer Institute, and gene-expression profiles were generated using 35K oligonucleotide microarrays. In addition, histopathological and immunohistochemical characterization was performed, and the findings were associated to clinical features.

RESULTS

All triple-negative tumors were classified as basal-like tumors on the basis of their overall gene-expression profile. Hierarchical cluster analysis revealed five distinct subgroups of triple-negative breast cancers. Multivariable analysis showed that a large amount of lymphocytic infiltrate (HR = 0.30, 95% CI 0.09-0.96) and absence of central fibrosis in the tumors (HR = 0.14, 95% CI 0.03-0.62) were associated with distant metastasis-free survival.

CONCLUSION

Triple-negative tumors are synonymous with basal-like tumors, and can be identified by immunohistochemistry. Based on gene-expression profiling, basal-like tumors are still heterogeneous and can be subdivided into at least five distinct subgroups. The development of distant metastasis in basal-like tumors is associated with the presence of central fibrosis and a small amount of lymphocytic infiltrate.

Genetic regulators of large-scale transcriptional signatures in cancer

Gene expression signatures encompassing dozens to hundreds of genes have been associated with many important parameters of cancer, but mechanisms of their control are largely unknown. Here we present a method based on genetic linkage that can prospectively identify functional regulators driving large-scale transcriptional signatures in cancer. Using this method we show that the wound response signature, a poor-prognosis expression pattern of 512 genes in breast cancer, is induced by coordinate amplifications of MYC and CSN5 (also known as JAB1 or COPS5). This information enabled experimental recapitulation, functional assessment and mechanistic elucidation of the wound signature in breast epithelial cells.

Lung tumor location and lymphocyte infiltration in mice are genetically determined

Lung cancer is a heterogeneous disease with individual differences in histological type, rate of progression, and response to therapy. Definition of the molecular and genetic basis of specific tumor characteristics would provide a better assessment of prognosis and a basis for a more individualized therapy. Here the authors compare the quantitative and qualitative phenotypes of lung tumors in mice of O20/A and OcB-9/Dem strains subjected to 2 regimens of N-ethyl-N-nitrosourea (ENU) treatment: (1) prenatal tumor induction by a single intraperitoneal (IP) injection of 40 mg/kg body weight into pregnant females and (2) after the same prenatal induction, the progeny received on weeks 9 and 11 additional IP ENU injections. The numbers, size, and histological characteristics of tumors were determined microscopically in semiserial lung sections. Unexpectedly, the authors observed very highly significant strain differences in a novel polymorphic phenotype-peribronchial versus nonperibronchial location of lung tumors, as well as in frequency of lymphocyte infiltration. To assess the reproducibility of these genetic differences, the authors classified both tumor location and lymphocyte infiltration also in an independent set of lung tumors that were induced in these strains in experiments performed more than 10 years ago in a different mouse facility and found the same strain differences. These results indicate that these qualitative phenotypes are very robust (P(c) 5.52 x 10(-6) and 2.27 x 10(-8), respectively) and relatively independent of environmental influences. They likely reflect different stages of lung differentiation at the time of tumor induction and differences in molecules involved in intercellular signaling, respectively. The definition of genes controlling these traits will provide novel insights into the determination of tumor phenotype.