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Fulltext Erratum: Publisher Correction: Homologous recombination DNA repair defects in PALB2-associated breast cancers

Li A, Geyer FC, Blecua P, Lee JY, Selenica P, Brown DN, et al.

NPJ Breast Cancer, 2019 11 19;5:44.
PMID: 31754629 DOI: 10.1038/s41523-019-0140-8

[This corrects the article DOI: 10.1038/s41523-019-0115-9.].
Fulltext Homologous recombination DNA repair defects in PALB2-associated breast cancers

Li A, Geyer FC, Blecua P, Lee JY, Selenica P, Brown DN, et al.

NPJ Breast Cancer, 2019;5:23.
PMID: 31428676 DOI: 10.1038/s41523-019-0115-9

Mono-allelic germline pathogenic variants in the Partner And Localizer of BRCA2 (PALB2) gene predispose to a high-risk of breast cancer development, consistent with the role of PALB2 in homologous recombination (HR) DNA repair. Here, we sought to define the repertoire of somatic genetic alterations in PALB2-associated breast cancers (BCs), and whether PALB2-associated BCs display bi-allelic inactivation of PALB2 and/or genomic features of HR-deficiency (HRD). Twenty-four breast cancer patients with pathogenic PALB2 germline mutations were analyzed by whole-exome sequencing (WES, n = 16) or targeted capture massively parallel sequencing (410 cancer genes, n = 8). Somatic genetic alterations, loss of heterozygosity (LOH) of the PALB2 wild-type allele, large-scale state transitions (LSTs) and mutational signatures were defined. PALB2-associated BCs were found to be heterogeneous at the genetic level, with PIK3CA (29%), PALB2 (21%), TP53 (21%), and NOTCH3 (17%) being the genes most frequently affected by somatic mutations. Bi-allelic PALB2 inactivation was found in 16 of the 24 cases (67%), either through LOH (n = 11) or second somatic mutations (n = 5) of the wild-type allele. High LST scores were found in all 12 PALB2-associated BCs with bi-allelic PALB2 inactivation sequenced by WES, of which eight displayed the HRD-related mutational signature 3. In addition, bi-allelic inactivation of PALB2 was significantly associated with high LST scores. Our findings suggest that the identification of bi-allelic PALB2 inactivation in PALB2-associated BCs is required for the personalization of HR-directed therapies, such as platinum salts and/or PARP inhibitors, as the vast majority of PALB2-associated BCs without PALB2 bi-allelic inactivation lack genomic features of HRD.
Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Page DB, Broeckx G, Jahangir CA, Verbandt S, Gupta RR, Thagaard J, et al.

J Pathol, 2023 Aug;260(5):514-532.
PMID: 37608771 DOI: 10.1002/path.6165

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.
Fulltext Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

Thagaard J, Broeckx G, Page DB, Jahangir CA, Verbandt S, Kos Z, et al.

J Pathol, 2023 Aug;260(5):498-513.
PMID: 37608772 DOI: 10.1002/path.6155

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.
Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer

Jahangir CA, Page DB, Broeckx G, Gonzalez CA, Burke C, Murphy C, et al.

J Pathol, 2024 Mar;262(3):271-288.
PMID: 38230434 DOI: 10.1002/path.6238

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.