Citations

Objectives Somatostatin receptor (SSTR) PET imaging is utilized with increasing frequency in the clinical management of neuroendocrine tumors. Incidental PET-avid CNS lesions are commonly noted and presumed to be meningiomas. However, SSTR PET lacks specificity for meningioma identification. This study aimed to clarify the role of SSTR-based imaging in the classification of incidental CNS lesions based on current clinical practice. Methods Patients who underwent both Ga-68-DOTATATE PET and brain MRI and had an incidental CNS lesion identified with a radiographic prediction of meningioma via one (discordant prediction) or both (concordant prediction) imaging modalities were retrospectively analyzed. Imaging indication, semiquantitative measures, and clinical history were recorded. Results Among 48 patients with a CNS lesion identified on both imaging modalities, most scans were performed for a history of neuroendocrine tumor (64.6%). Cases with concordant lesion-type prediction of meningioma between imaging modalities (N = 24) displayed a significantly higher SUV max (median 7.9 vs. 4.0; P = 0.008) and Krenning score (median 3.0 vs. 2.0; P = 0.005) on Ga-68-DOTATATE PET compared with cases with a discordant prediction of meningioma (N = 24). In cases with lower SUV max values, Ga-68-DOTATATE was more likely to discordantly predict meningioma without agreement by the corresponding MRI. Prior cranial radiation or use of somatostatin mimetics did not affect quantitative radiographic measures, and MRI-based tumor size was similar across groups. Conclusion Lesions with increased avidity may be more confidently predicted as meningioma in Ga-68-DOTATATE PET scans, whereas there is more discrepancy in prediction among low SUV cases.

Abstract Adenocarcinoma (ADC) and Squamous Cell Carcinoma (SCC) are the most frequent histologic subtypes of lung cancer, and both are rich in activated/myofibroblast-like tumor-associated fibroblasts (TAFs). Nintedanib is a potent antifibrotic drug that targets the tumor stroma and is clinically approved to treat advanced lung ADC patients owing to the survival benefits observed in the LUME-1 clinical trial in ADC but not SCC patients. Although the mechanism underlying the ADC-selective therapeutic effects of nintedanib remained poorly understood, we have previously reported that nintedanib abrogates the pro-tumoral traits of the secretome of ADC-TAFs but not SCC-TAFs, suggesting that secreted factor(s) in ADC-TAFs may be implicated. In addition, we recently unveiled an ADC-specific tumor-promoting crosstalk between TAFs and cancer cells driven by TIMP-1 and CD63, whereas others have shown that TIMP-1 is a molecular target of nintedanib. However, it remains unknown if TIMP-1 is involved in the ADC-selective benefits of nintedanib. To address this question, we used patient-derived TAFs obtained with the patient’s informed consent and using protocols approved by the Ethics Committee of the Hospital Clinic. We treated TGF-β1-activated ADC-TAFs and SCC-TAFs with nintedanib and determined the content of TIMP-1 in their conditioned medium by ELISA. Moreover, we used cell-based functional assays and tumor xenografts after knocking-down TIMP-1 in TAFs by siRNA to examine how silencing TIMP-1 altered their response to nintedanib. By analyzing TCGA data and the human protein atlas, we found that TIMP-1 is consistently upregulated in ADC compared to SCC tumors both at the mRNA and protein levels. Moreover, TCGA data revealed that TIMP-1 is increased in tumors compared to paired control tissue in ADC but not SCC. In culture, we observed that TIMP-1 secretion was higher in ADC-TAFs than SCC-TAFs, and that this secretion was downregulated by nintedanib to a larger extent in ADC-TAFs compared to SCC-TAFs. In vivo analyses revealed that ADC cells co-injected with fibroblasts silenced for TIMP-1 as in SCC-TAFs into immunocompromised mice exhibited a less invasive growth pattern compared to tumors bearing control fibroblasts. In addition, we observed that the inhibition of the pro-tumoral secretome of ADC-TAFs elicited by nintedanib was abrogated upon knocking-down TIMP-1 in TAFs both in vitro and in vivo. Collectively, these results reveal that the high secretion of TIMP-1 in ADC-TAFs render them more responsive to nintedanib, whereas the low TIMP-1 secretion of SCC-TAFs may be a major contributor to the selective resistance of SCC patients to nintedanib. Moreover, our results identify TIMP-1 as a promising predictive biomarker of nintedanib responses. Citation Format: Paula Duch, Natalia Díaz-Valdivia, Marta Gabasa, Rafael Ikemori, Frank Hilberg, Noemí Reguart, Derek Radisky, Jordi Alcaraz. Aberrant TIMP-1 secretion by tumor-associated fibroblasts is a major contributor to the selective positive response to nintedanib in lung adenocarcinoma [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 2356.

Abstract Purpose: Benign breast disease (BBD) is viewed as a non-obligate precursor stage in the development of breast cancer (BC). Transcriptome profiling using RNA sequencing (RNA-seq) of bulk formalin-fixed paraffin-embedded (FFPE) tissue blocks has been routinely used in BC research. However, RNA-seq of heterogeneous bulk samples represents an averaged expression profile across all cell mixtures. Downstream analyses, such as biomarker discovery, are likely confounded by differences in cell proportions. There is a lack of research in optimizing strategies for cell type deconvolution especially for FFPE samples. We evaluated and optimized strategies for cell type deconvolution using existing single cell RNA-seq (scRNA-seq) and single nucleus RNA-seq (snRNA-seq) breast tissue references, and applied these to a cohort of BBD FFPE samples to assess risk of subsequent BC. Methods: 7 scRNA-seq and 3 snRNA-seq public samples from women’s breast tissue were normalized using SCTransform, then integrated using Harmony to form a complete reference set. Bioinformatics evaluations examined the performance of existing statistical and deep learning-based deconvolution methods. Computational simulations were conducted to evaluate those methods on three scenarios: 1) baseline; 2) incomplete reference set; 3) FFPE artifacts. FFPE artifacts were simulated based on a generalized additive model using 7 in-house paired FFPE-fresh frozen samples. Finally, we applied the best performing method to our BBD cohort of 62 samples. Differential expression analysis adjusting for cell proportions was performed to identify transcriptomic aberrations in BBD cases. Results: snRNA-seq was more sensitive in capturing adipocytes, while scRNA-seq was more sensitive in detecting lymphocytes in breast tissue. The median number of detectable genes per cell was higher for scRNA-seq than snRNA-seq before integration (1264 vs 558). Marker gene-based regression methods (e.g. CIBERSORT) displayed higher variance and lower bias compared to methods directly using scRNA-seq data (e.g. SCDC). Incomplete reference data led to increased bias and little effect on variance. FFPE artifacts had a higher impact on performance compared to incomplete reference data. Overall, Scaden, a deep learning-based method, was the top performing method across all simulation scenarios and was especially robust to FFPE artifacts. 59 differential expressed genes (DEGs) were identified with fold change > 1.5 and p value < 0.01. DEGs involved in BC, e.g. S100A8, WNT4 and HIST1H3H, would be left out if cell proportions were not properly adjusted. Conclusions: We constructed the first complete single cell reference data for women’s breast tissue and benchmarked existing cell type deconvolution methods. Compared to analyses not adjusting for cell proportions, we observed substantial differences in perturbed genes and pathways associated with BC risk for BBD patients. Citation Format: Yuanhang Liu, Chen Wang, Stacey J. Winham, Aditya Bhagwate, Robert A. Vierkant, Julie M. Cunningham, Bryan M. McCauley, William A. Jons, Derek C. Radisky, Amy C. Degnim. Deconvolution of cell type composition in FFPE tissue: Application to benign breast disease. [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 4291.

Abstract Purpose: Young women’s breast cancers (YBCs), defined herein as breast cancer (BC) diagnosed at age ≤ 40 years, are etiologically and biologically distinct from postmenopausal BCs, demonstrating a higher proportion of estrogen receptor (ER) negative subtypes and a worse prognosis. Studies have not assessed whether risk factors such as recent parity and body mass index (BMI) are linked to protein expression profiles in YBCs. Accordingly, we examined protein expression assessed with GeoMx® Digital Spatial Profiling (DSP) in 640 YBCs prepared as tissue microarrays (TMAs) in the Young Women’s BC Study (YWBCS). Methods: The YWBCS is a multi-institutional cohort of 1,297 women with incident BC diagnosed at age <40 years identified through medical record review, with risk factor data collected via questionnaires. TMAs including 1,505 cores of 640 YBCs that were collected prior to therapy and were suitable for molecular analysis were evaluated for 72 markers with NanoString GeoMx DSP. Associations of log-transformed biomarker expression with BMI and time from last live birth to BC diagnosis were carried out using linear mixed modeling approaches, accounting for multiple tumor tissue cores per individual. Results: Mean age at BC was 35.5 years (range 17-40). Tumor subtypes based on clinical immunostaining were the following: luminal B 46%; luminal A 36%; triple negative 12% and HER2+ 6%. Of 72 biomarkers tested, 53 (74%) were evaluable after QC and normalization. GeoMx ER and PR protein levels were higher in luminal A and luminal B YBCs than in HER2+ and TNBC (p=2x10-94 and 2x10-52, respectively), supporting the accuracy of the GeoMx assay. Compared to nulliparas or those with most recent birth > 3 years before BC, those who gave birth ≤ 3 years prior to BC had tumors with higher expression of PR (8x10-6) and ER (p=0.006), and lower expression of BCL-2 (p=0.006). In contrast, women with last birth ≥ 6 years prior to BC had higher expression of CD8 (p=0.006) and PD-1 (p=0.001) than nulliparas and those with more recent births. Compared to women with BMI between 18.5 and 29.9, those with higher or lower BMIs had higher expression of CD34 (p=0.0003), CD4 (p=0.0009) and CD14 (p=0.001). BCL-2 expression was higher among women with BMI < 18.5 compared to those with higher values (p=0.005). Women with BMI of 30+ had higher β2-microglobulin levels than those with lower BMIs (p=0.003). Inverse dose-response associations (with higher BMI related to lower levels) were observed for expression of ER (p=0.01), pan cytokeratin (p=0.004) and four proteins in the p13K/AKT signaling pathway (p ≤ 0.01 for each). Conclusions: Preliminarily, we identify differences in hormonal and immune markers in YBCs in relation to timing of births and BMI, suggesting that these factors may contribute to etiologic heterogeneity. Multivariate modeling is ongoing to incorporate molecular subtype and other risk factors. Citation Format: Robert A. Vierkant, Laura M. Pacheco-Spann, Stacey J. Winham, Jennifer M. Kachergus, Ji Shi, Craig Snow, Fergus J. Couch, Janet E. Olson, Chen Wang, Derek C. Radisky, Amy C. Degnim, E. Aubrey Thompson, Laura C. Collins, Kathryn J. Ruddy, Ann H. Partridge, Mark E. Sherman. Associations of parity and body mass index with NanoString digital spatial protein profiling in early onset breast cancer [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 1000.

AbstractIntroductionFor too many people, their care plans are designed without fully accounting for who they are, the lives they live, what matters to them or what they aspire to achieve. We aimed to summarize instruments capable of measuring dimensions of patient–clinician collaboration to make care fit.MethodsWe systematically searched several databases (Medline, Embase, Cochrane, Scopus and Web of Science) from inception to September 2021 for studies using quantitative measures to assess, evaluate or rate the work of making care fit by any participant in real‐life clinical encounters. Eligibility was assessed in duplicate. After extracting all items from relevant instruments, we coded them deductively on dimensions relevant to making care fit (as presented in a recent Making Care Fit Manifesto), and inductively on the main action described.ResultsWe included 189 papers, mostly from North America (N = 83, 44%) and in the context of primary care (N = 54, 29%). Half of the papers (N = 88, 47%) were published in the last 5 years. We found 1243 relevant items to assess efforts of making care fit, included within 151 instruments. Most items related to the dimensions ‘Patient‐clinician collaboration: content’ (N = 396, 32%) and ‘Patient‐clinician collaboration: manner’ (N = 382, 31%) and the least related to ‘Ongoing and iterative process’ (N = 22, 2%) and in ‘Minimally disruptive of patient lives’ (N = 29, 2%). The items referred to 27 specific actions. Most items referred to ‘Informing’ (N = 308, 25%) and ‘Exploring’ (N = 93, 8%), the fewest items referred to ‘Following up’, ‘Comforting’ and ‘Praising’ (each N = 3, 0.2%).DiscussionMeasures of the work that patients and clinicians do together to make care fit focus heavily on the content of their collaborations, particularly on exchanging information. Other dimensions and actions previously identified as crucial to making care fit are assessed infrequently or not at all. The breadth of extant measures of making care fit and the lack of appropriate measures of this key construct limit both the assessment and the successful implementation of efforts to improve patient care.Patient ContributionPatients and caregivers from the ‘Making care fit Collaborative’ were involved in drafting the dimensions relevant to patient–clinician collaboration.

Breast cancer is a significant cause of morbidity and mortality in women, with over two million new cases reported worldwide each year, the majority of which occur in post-menopausal women. Despite advances in early detection and treatment, approximately one-third of patients diagnosed with breast cancer will develop metastatic disease. The pathogenesis and progression of breast cancer are influenced by a variety of biological and social risk factors, including age, ethnicity, pregnancy status, diet, and genomic alterations. Recent advancements in breast cancer research have focused on harnessing the power of the patient’s adaptive and innate immune systems for diagnostic and therapeutic purposes. The breast immune microenvironment plays a critical role in regulating tissue homeostasis and resistance to tumorigenesis. In this review, we explore the dynamic changes in the breast immune microenvironment that occur with age, how these changes impact breast cancer development and progression, and how targeted therapeutic interventions that leverage the immune system can be used to improve patient outcomes. Our review emphasizes the importance of understanding the complex interplay between aging, the immune system, and breast cancer, and highlights the potential of immune-based therapies in the fight against this devastating disease.