Showing papers by "Hugo M. Horlings published in 2020"

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer.

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

Report on computational assessment of Tumor Infiltrating Lymphocytes from the International Immuno-Oncology Biomarker Working Group

Abstract: Assessment of tumor-infiltrating lymphocytes (TILs) is increasingly recognized as an integral part of the prognostic workflow in triple-negative (TNBC) and HER2-positive breast cancer, as well as many other solid tumors. This recognition has come about thanks to standardized visual reporting guidelines, which helped to reduce inter-reader variability. Now, there are ripe opportunities to employ computational methods that extract spatio-morphologic predictive features, enabling computer-aided diagnostics. We detail the benefits of computational TILs assessment, the readiness of TILs scoring for computational assessment, and outline considerations for overcoming key barriers to clinical translation in this arena. Specifically, we discuss: 1. ensuring computational workflows closely capture visual guidelines and standards; 2. challenges and thoughts standards for assessment of algorithms including training, preanalytical, analytical, and clinical validation; 3. perspectives on how to realize the potential of machine learning models and to overcome the perceptual and practical limits of visual scoring.

Reversal of pre-existing NGFR-driven tumor and immune therapy resistance

Abstract: Melanomas can switch to a dedifferentiated cell state upon exposure to cytotoxic T cells. However, it is unclear whether such tumor cells pre-exist in patients and whether they can be resensitized to immunotherapy. Here, we chronically expose (patient-derived) melanoma cell lines to differentiation antigen-specific cytotoxic T cells and observe strong enrichment of a pre-existing NGFRhi population. These fractions are refractory also to T cells recognizing non-differentiation antigens, as well as to BRAF + MEK inhibitors. NGFRhi cells induce the neurotrophic factor BDNF, which contributes to T cell resistance, as does NGFR. In melanoma patients, a tumor-intrinsic NGFR signature predicts anti-PD-1 therapy resistance, and NGFRhi tumor fractions are associated with immune exclusion. Lastly, pharmacologic NGFR inhibition restores tumor sensitivity to T cell attack in vitro and in melanoma xenografts. These findings demonstrate the existence of a stable and pre-existing NGFRhi multitherapy-refractory melanoma subpopulation, which ought to be eliminated to revert intrinsic resistance to immunotherapeutic intervention. Dedifferentiation state has been associated with therapy resistance in melanoma. Here, the authors uncover a pre-existing NGFR-expressing, targetable subpopulation that is resistant to immunotherapy and other treatments in melanoma cells and preclinical models.

The NF-κB Pathway Promotes Tamoxifen Tolerance and Disease Recurrence in Estrogen Receptor-Positive Breast Cancers.

Abstract: The purpose of this study was to identify critical pathways promoting survival of tamoxifen-tolerant, estrogen receptor α positive (ER+) breast cancer cells, which contribute to therapy resistance and disease recurrence. Gene expression profiling and pathway analysis was performed in ER+ breast tumors of patients before and after neo-adjuvant tamoxifen treatment and demonstrated activation of the NFκB pathway and an enrichment of EMT/stemness features. Exposure of ER+ breast cancer cell lines to tamoxifen, in vitro and in vivo, gives rise to a tamoxifen-tolerant population with similar NFκB activity and EMT/stemness characteristics. Small molecule inhibitors and CRISPR/Cas9 knock out were used to assess the role of the nuclear factor κB (NFκB) pathway and demonstrated that survival of tamoxifen-tolerant cells requires NFκB activity. Moreover, this pathway was essential for tumor recurrence following tamoxifen withdrawal. These findings establish that elevated NFκB activity is observed in breast cancer cell lines under selective pressure with tamoxifen in vitro and in vivo, as well as in patient tumors treated with neo-adjuvant tamoxifen therapy. This pathway is essential for survival and regrowth of tamoxifen-tolerant cells, and, as such, NFκB inhibition offers a promising approach to prevent recurrence of ER+ tumors following tamoxifen exposure. Implications: Understanding initial changes that enable survival of tamoxifen-tolerant cells, as mediated by NFκB pathway, may translate into therapeutic interventions to prevent resistance and relapse, which remain major causes of breast cancer lethality.

Characteristics and Outcome of AKT1E17K-Mutant Breast Cancer Defined through AACR Project GENIE, a Clinicogenomic Registry

Abstract: AKT inhibitors have promising activity in AKT1E17K-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 AKT1E17K-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, AKT1E17K-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.

Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials

Abstract: Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting.

Functional Profiling of FSH and Estradiol in Ovarian Granulosa Cell Tumors.

Abstract: Adult-type granulosa cell tumors (AGCTs) are sex-cord derived neoplasms with a propensity for late relapse. Hormonal modulators have been used empirically in the treatment of recurrent AGCT, albeit with limited success. To provide a more rigorous foundation for hormonal therapy in AGCT, we used a multimodal approach to characterize the expressions of key hormone biomarkers in 175 tumor specimens and 51 serum samples using RNA sequencing, immunohistochemistry, RNA in situ hybridization, quantitative PCR, and circulating biomarker analysis, and correlated these results with clinical data. We show that FSH receptor and estrogen receptor beta (ERβ) are highly expressed in the majority of AGCTs, whereas the expressions of estrogen receptor alpha (ERα) and G-protein coupled estrogen receptor 1 are less prominent. ERβ protein expression is further increased in recurrent tumors. Aromatase expression levels show high variability between tumors. None of the markers examined served as prognostic biomarkers for progression-free or overall survival. In functional experiments, we assessed the effects of FSH, estradiol (E2), and the aromatase inhibitor letrozole on AGCT cell viability using 2 in vitro models: KGN cells and primary cultures of AGCT cells. FSH increased cell viability in a subset of primary AGCT cells, whereas E2 had no effect on cell viability at physiological concentrations. Letrozole suppressed E2 production in AGCTs; however, it did not impact cell viability. We did not find preclinical evidence to support the clinical use of aromatase inhibitors in AGCT treatment, and thus randomized, prospective clinical studies are needed to clarify the role of hormonal treatments in AGCTs.

The effect of the peritoneal tumor microenvironment on invasion of peritoneal metastases of high-grade serous ovarian cancer and the impact of NEOADJUVANT chemotherapy.

Abstract: Peritoneal metastases of high-grade serous ovarian cancer (HGSOC) are small-sized deposits with superficial growth toward the peritoneal cavity. It is unknown whether integrity of the peritoneal elastic lamina (PEL) correlates with the peritoneal tumor microenvironment (pTME) and whether neoadjuvant chemotherapy (NACT) affects the pTME. We explored integrity of PEL, composition of pTME, effects of NACT, and the prognostic implications in patients with extensive peritoneal metastases of HGSOC. Peritoneal samples (n = 69) were collected during cytoreductive surgery between 2003 and 2016. Clinical data were collected from medical charts. Integrity of PEL was evaluated with elastic stains. T cell (CD3, CD8) and M2-macrophage markers (CD163) were scored using algorithms created in definiens tissue studio. Patients with a disrupted PEL (n = 39; 57%), more often had residual disease after surgery (p = 0.050), compared to intact PEL. An intact PEL was associated with increased intraepithelial (ie) CD8+ cells (p = 0.032), but was not correlated with improved survival. After NACT, increased ieCD3+ cells were shown, compared to no-NACT (p = 0.044). Abundance of total CD3+ and CD8+ cells were associated with PFS (multivariate HR 0.40; 95%CI 0.23-0.69 and HR 0.49; 95%CI 0.29-0.83) and OS (HR 0.33; 95%CI 0.18-0.62 and HR 0.36; 95%CI 0.20-0.64). M2-macrophage infiltration was not correlated with survival. NACT increases abundance of ieCD3+ cells in peritoneal metastases of HGSOC. Increase of CD3+ and CD8+ cells is associated with improved PFS and OS. This suggests that CD3+ and CD8+ cells may function as prognostic biomarkers. Their role as predictive biomarker for chemotherapy or immunotherapy response in HGSOC warrants further research.

Automated Scoring of Nuclear Pleomorphism Spectrum with Pathologist-level Performance in Breast Cancer.

Abstract: Nuclear pleomorphism, defined herein as the extent of abnormalities in the overall appearance of tumor nuclei, is one of the components of the three-tiered breast cancer grading. Given that nuclear pleomorphism reflects a continuous spectrum of variation, we trained a deep neural network on a large variety of tumor regions from the collective knowledge of several pathologists, without constraining the network to the traditional three-category classification. We also motivate an additional approach in which we discuss the additional benefit of normal epithelium as baseline, following the routine clinical practice where pathologists are trained to score nuclear pleomorphism in tumor, having the normal breast epithelium for comparison. In multiple experiments, our fully-automated approach could achieve top pathologist-level performance in select regions of interest as well as at whole slide images, compared to ten and four pathologists, respectively.