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Kameyama H, Dondapati P, Simmons R, Leslie M, Langenheim JF, Sun Y, Yi M, Rottschaefer A, Pathak R, Nuguri S, Fung KM, Tsaih SW, Chervoneva I, Rui H, Tanaka T. Needle biopsy accelerates pro-metastatic changes and systemic dissemination in breast cancer: Implications for mortality by surgery delay. Cell Rep Med 2023; 4:101330. [PMID: 38118415 PMCID: PMC10772461 DOI: 10.1016/j.xcrm.2023.101330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/14/2022] [Accepted: 11/17/2023] [Indexed: 12/22/2023]
Abstract
Increased breast cancer (BC) mortality risk posed by delayed surgical resection of tumor after diagnosis is a growing concern, yet the underlying mechanisms remain unknown. Our cohort analyses of early-stage BC patients reveal the emergence of a significantly rising mortality risk when the biopsy-to-surgery interval was extended beyond 53 days. Additionally, histology of post-biopsy tumors shows prolonged retention of a metastasis-permissive wound stroma dominated by M2-like macrophages capable of promoting cancer cell epithelial-to-mesenchymal transition and angiogenesis. We show that needle biopsy promotes systemic dissemination of cancer cells through a mechanism of sustained activation of the COX-2/PGE2/EP2 feedforward loop, which favors M2 polarization and its associated pro-metastatic changes but are abrogated by oral treatment with COX-2 or EP2 inhibitors in estrogen-receptor-positive (ER+) syngeneic mouse tumor models. Therefore, we conclude that needle biopsy of ER+ BC provokes progressive pro-metastatic changes, which may explain the mortality risk posed by surgery delay after diagnosis.
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Affiliation(s)
- Hiroyasu Kameyama
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - Priya Dondapati
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - Reese Simmons
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - Macall Leslie
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - John F Langenheim
- Department of Pharmacology, Physiology & Cancer Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, 233 S 10th St., BLSB 1008, Philadelphia, PA 19107, USA
| | - Yunguang Sun
- Department of Pathology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA
| | - Misung Yi
- Division of Biostatistics, Department of Pharmacology, Physiology & Cancer Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, 233 S 10th St., BLSB 1008, Philadelphia, PA 19107, USA
| | - Aubrey Rottschaefer
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - Rashmi Pathak
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - Shreya Nuguri
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA
| | - Kar-Ming Fung
- Department of Pathology, School of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L Young Boulevard, Oklahoma City, OK 73104, USA
| | - Shirng-Wern Tsaih
- Department of Obstetrics and Gynecology, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA
| | - Inna Chervoneva
- Division of Biostatistics, Department of Pharmacology, Physiology & Cancer Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, 233 S 10th St., BLSB 1008, Philadelphia, PA 19107, USA
| | - Hallgeir Rui
- Department of Pharmacology, Physiology & Cancer Biology, Sidney Kimmel Cancer Center, Thomas Jefferson University, 233 S 10th St., BLSB 1008, Philadelphia, PA 19107, USA
| | - Takemi Tanaka
- Stephenson Cancer Center, University of Oklahoma Health Sciences Center, 975 NE 10th St., Oklahoma City, OK 73104, USA; Department of Pathology, School of Medicine, University of Oklahoma Health Sciences Center, 940 Stanton L Young Boulevard, Oklahoma City, OK 73104, USA.
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Yi M, Zhan T, Peck AR, Hooke JA, Kovatich AJ, Shriver CD, Hu H, Sun Y, Rui H, Chervoneva I. Quantile Index Biomarkers Based on Single-Cell Expression Data. J Transl Med 2023; 103:100158. [PMID: 37088463 PMCID: PMC10524910 DOI: 10.1016/j.labinv.2023.100158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 04/06/2023] [Accepted: 04/15/2023] [Indexed: 04/25/2023] Open
Abstract
Current histocytometry methods enable single-cell quantification of biomolecules in tumor tissue sections by multiple detection technologies, including multiplex fluorescence-based immunohistochemistry or in situ hybridization. Quantitative pathology platforms can provide distributions of cellular signal intensity (CSI) levels of biomolecules across the entire cell populations of interest within the sampled tumor tissue. However, the heterogeneity of CSI levels is usually ignored, and the simple mean signal intensity value is considered a cancer biomarker. Here we consider the entire distribution of CSI expression levels of a given biomolecule in the cancer cell population as a predictor of clinical outcome. The proposed quantile index (QI) biomarker is defined as the weighted average of CSI distribution quantiles in individual tumors. The weight for each quantile is determined by fitting a functional regression model for a clinical outcome. That is, the weights are optimized so that the resulting QI has the highest power to predict a relevant clinical outcome. The proposed QI biomarkers were derived for proteins expressed in cancer cells of malignant breast tumors and demonstrated improved prognostic value compared with the standard mean signal intensity predictors. The R package Qindex implementing QI biomarkers has been developed. The proposed approach is not limited to immunohistochemistry data and can be based on any cell-level expressions of proteins or nucleic acids.
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Affiliation(s)
- Misung Yi
- Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania.
| | - Tingting Zhan
- Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Amy R Peck
- Department of Pathology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Jeffrey A Hooke
- John P. Murtha Cancer Center, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, Maryland
| | - Albert J Kovatich
- John P. Murtha Cancer Center, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, Maryland
| | - Craig D Shriver
- John P. Murtha Cancer Center, Uniformed Services University and Walter Reed National Military Medical Center, Bethesda, Maryland
| | - Hai Hu
- Chan Soon-Shiong Institute of Molecular Medicine at Windber, Windber, Pennsylvania
| | - Yunguang Sun
- Department of Pathology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Hallgeir Rui
- Department of Pathology, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Inna Chervoneva
- Division of Biostatistics, Department of Pharmacology and Experimental Therapeutics, Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, Pennsylvania.
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Tumedei MM, Piccinini F, Azzali I, Pirini F, Bravaccini S, De Matteis S, Agostinelli C, Castellani G, Zanoni M, Cortesi M, Vergani B, Leone BE, Righi S, Gazzola A, Casadei B, Gentilini D, Calzari L, Limarzi F, Sabattini E, Pession A, Tazzari M, Bertuzzi C. Follicular Lymphoma Microenvironment Traits Associated with Event-Free Survival. Int J Mol Sci 2023; 24:9909. [PMID: 37373066 DOI: 10.3390/ijms24129909] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/26/2023] [Accepted: 06/01/2023] [Indexed: 06/29/2023] Open
Abstract
The majority of patients with Follicular Lymphoma (FL) experience subsequent phases of remission and relapse, making the disease "virtually" incurable. To predict the outcome of FL patients at diagnosis, various clinical-based prognostic scores have been proposed; nonetheless, they continue to fail for a subset of patients. Gene expression profiling has highlighted the pivotal role of the tumor microenvironment (TME) in the FL prognosis; nevertheless, there is still a need to standardize the assessment of immune-infiltrating cells for the prognostic classification of patients with early or late progressing disease. We studied a retrospective cohort of 49 FL lymph node biopsies at the time of the initial diagnosis using pathologist-guided analysis on whole slide images, and we characterized the immune repertoire for both quantity and distribution (intrafollicular, IF and extrafollicular, EF) of cell subsets in relation to clinical outcome. We looked for the natural killer (CD56), T lymphocyte (CD8, CD4, PD1) and macrophage (CD68, CD163, MA4A4A)-associated markers. High CD163/CD8 EF ratios and high CD56/MS4A4A EF ratios, according to Kaplan-Meier estimates were linked with shorter EFS (event-free survival), with the former being the only one associated with POD24. In contrast to IF CD68+ cells, which represent a more homogeneous population, higher in non-progressing patients, EF CD68+ macrophages did not stratify according to survival. We also identify distinctive MS4A4A+CD163-macrophage populations with different prognostic weights. Enlarging the macrophage characterization and combining it with a lymphoid marker in the rituximab era, in our opinion, may enable prognostic stratification for low-/high-grade FL patients beyond POD24. These findings warrant validation across larger FL cohorts.
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Affiliation(s)
- Maria Maddalena Tumedei
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Filippo Piccinini
- Scientific Directorate, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40126 Bologna, Italy
| | - Irene Azzali
- Biostatistics and Clinical Trials Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Francesca Pirini
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Sara Bravaccini
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Serena De Matteis
- Immunobiology of Transplants and Advanced Cellular Therapies Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Claudio Agostinelli
- Hematopathology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Gastone Castellani
- Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40126 Bologna, Italy
| | - Michele Zanoni
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Michela Cortesi
- Biosciences Laboratory, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Barbara Vergani
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
| | - Biagio Eugenio Leone
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
| | - Simona Righi
- Hematology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Anna Gazzola
- Hematology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Beatrice Casadei
- Hematology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Davide Gentilini
- Department of Brain and Behavioral Sciences, Università di Pavia, 27100 Pavia, Italy
- Bioinformatics and Statistical Genomics Unit, Istituto Auxologico Italiano IRCCS, 20095 Cusano Milanino, Italy
| | - Luciano Calzari
- Bioinformatics and Statistical Genomics Unit, Istituto Auxologico Italiano IRCCS, 20095 Cusano Milanino, Italy
| | - Francesco Limarzi
- Pathology Unit, Morgagni-Pierantoni Hospital, AUSL Romagna, Via Carlo Forlanini, 34, 47121 Forlì, Italy
| | - Elena Sabattini
- Hematology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Andrea Pession
- Department of Pediatrics, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
| | - Marcella Tazzari
- Immunotherapy Cell Therapy and Biobank (ITCB) Unit, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) "Dino Amadori", 47014 Meldola, Italy
| | - Clara Bertuzzi
- Hematopathology Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, 40138 Bologna, Italy
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Wrobel J, Harris C, Vandekar S. Statistical Analysis of Multiplex Immunofluorescence and Immunohistochemistry Imaging Data. Methods Mol Biol 2023; 2629:141-168. [PMID: 36929077 DOI: 10.1007/978-1-0716-2986-4_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Advances in multiplexed single-cell immunofluorescence (mIF) and multiplex immunohistochemistry (mIHC) imaging technologies have enabled the analysis of cell-to-cell spatial relationships that promise to revolutionize our understanding of tissue-based diseases and autoimmune disorders. Multiplex images are collected as multichannel TIFF files; then denoised, segmented to identify cells and nuclei, normalized across slides with protein markers to correct for batch effects, and phenotyped; and then tissue composition and spatial context at the cellular level are analyzed. This chapter discusses methods and software infrastructure for image processing and statistical analysis of mIF/mIHC data.
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Affiliation(s)
- Julia Wrobel
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Coleman Harris
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
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Ma S, Zhao Y, Liu X, Sun Zhang A, Zhang H, Hu G, Sun XF. CD163 as a Potential Biomarker in Colorectal Cancer for Tumor Microenvironment and Cancer Prognosis: A Swedish Study from Tissue Microarrays to Big Data Analyses. Cancers (Basel) 2022; 14:cancers14246166. [PMID: 36551651 PMCID: PMC9776587 DOI: 10.3390/cancers14246166] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/01/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022] Open
Abstract
(1) Background: CD163, a specific macrophage receptor, affects the progression of malignant tumors. Unfortunately, the regulation and expression of CD163 are poorly understood. In this study, we determined the expressions of CD163 in TMA samples from CRC patients and combined them with patient data from several Swedish hospitals. (2) Methods: The expressions of CD163 in tissue samples from CRC patients were examined. After combining 472 CRC patients’ gene expression and 438 CRC patients’ clinical data with the TCGA database, 964 cases from the GEO database, and experimental expression data from 1247 Swedish CRC patients, we selected four genes (PCNA, LOX, BCL2, and CD163) and analyzed the tumor-infiltrating immune cells (TICs) and CRC prognosis. (3) Results: Based on histopathological TMA analysis, CD163 was strongly expressed in the stroma of both normal and cancer tissues, and the expressions in normal and cancer cells varied from negative to strong. The results from public databases show decreased expression of CD163 in cancer tissue compared to normal mucosa (|log FC| > 1 and FDR < 0.01), and it is a negative prognostic factor for CRC patients (p-value < 0.05). Through tumor microenvironment (TME) analysis, we found a potential influence of CD163 on immune cell infiltration. Furthermore, the enrichment analysis indicated the possible interaction with other proteins and biological pathways. (4) Conclusions: CD163 is expressed differently in CRC tissue and is a negative prognostic factor. Its expression is associated with the TME and tumor purity of CRC. Considering all results, CD163 has the potential to be a predictive biomarker in the investigation of CRC.
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Affiliation(s)
- Shuwen Ma
- Institute of Environmental Medicine, Karolinska Institute, SE-171 77 Stockholm, Sweden
| | - Yuxin Zhao
- Department of Epidemiology, School of Public Health, China Medical University, Shenyang 110122, China
| | - Xingyi Liu
- Centre for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215006, China
| | - Alexander Sun Zhang
- Department of Oncology-Pathology, Karolinska Institute, SE-171 77 Stockholm, Sweden
| | - Hong Zhang
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, SE-701 82 Örebro, Sweden
| | - Guang Hu
- Centre for Systems Biology, Department of Bioinformatics, School of Biology and Basic Medical Sciences, Soochow University, Suzhou 215006, China
| | - Xiao-Feng Sun
- Department of Oncology, and Department of Biomedical and Clinical Sciences, Linköping University, SE-581 83 Linköping, Sweden
- Correspondence:
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Tumor-promoting aftermath post-chemotherapy: A focus on breast cancer. Life Sci 2022; 310:121125. [DOI: 10.1016/j.lfs.2022.121125] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 10/14/2022] [Accepted: 10/22/2022] [Indexed: 11/09/2022]
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Tosi A, Parisatto B, Menegaldo A, Spinato G, Guido M, Del Mistro A, Bussani R, Zanconati F, Tofanelli M, Tirelli G, Boscolo-Rizzo P, Rosato A. The immune microenvironment of HPV-positive and HPV-negative oropharyngeal squamous cell carcinoma: a multiparametric quantitative and spatial analysis unveils a rationale to target treatment-naïve tumors with immune checkpoint inhibitors. J Exp Clin Cancer Res 2022; 41:279. [PMID: 36123711 PMCID: PMC9487049 DOI: 10.1186/s13046-022-02481-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/30/2022] [Indexed: 11/27/2022] Open
Abstract
Background Immune checkpoint inhibitors (ICI) are approved for treatment of recurrent or metastatic oropharyngeal head and neck squamous cell carcinoma in the first- and second-line settings. However, only 15–20% of patients benefit from this treatment, a feature increasingly ascribed to the peculiar characteristics of the tumor immune microenvironment (TIME). Methods Immune-related gene expression profiling (GEP) and multiplex immunofluorescence (mIF) including spatial proximity analysis, were used to characterize the TIME of 39 treatment-naïve oropharyngeal squamous cell carcinomas (OPSCC) and the corresponding lymph node metastases. GEP and mIF results were correlated with disease-free survival (DFS). HPV-positive tumors disclosed a stronger activation of several immune signalling pathways, as well as a higher expression of genes related to total tumor-infiltrating lymphocytes, CD8 T cells, cytotoxic cells and exhausted CD8 cells, than HPV-negative patients. Accordingly, mIF revealed that HPV-positive lesions were heavily infiltrated as compared to HPV-negative counterparts, with a higher density of T cells and checkpoint molecules. CD8+ T cells appeared in closer proximity to tumor cells, CD163+ macrophages and FoxP3+ cells in HPV-positive primary tumors, and related metastases. In HPV-positive lesions, PD-L1 expression was increased as compared to HPV-negative samples, and PD-L1+ tumor cells and macrophages were closer to PD-1+ cytotoxic T lymphocytes. Considering the whole cohort, a positive correlation was observed between DFS and higher levels of activating immune signatures and T cell responses, higher density of PD-1+ T cells and their closer proximity to tumor cells or PD-L1+ macrophages. HPV-positive patients with higher infiltration of T cells and macrophages had a longer DFS, while CD163+ macrophages had a negative role in prognosis of HPV-negative patients. Conclusions Our results suggest that checkpoint expression may reflect an ongoing antitumor immune response. Thus, these observations provide the rationale for the incorporation of ICI in the loco-regional therapy strategies for patients with heavily infiltrated treatment-naïve OPSCC, and for the combination of ICI with tumor-specific T cell response inducers or TAM modulators for the “cold” OPSCC counterparts. Supplementary Information The online version contains supplementary material available at 10.1186/s13046-022-02481-4.
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