| 1. |
- Pereira, Carla, et al.
(author)
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Comparison of East‐Asia and West‐Europe cohorts explains disparities in survival outcomes and highlights predictive biomarkers of early gastric cancer aggressiveness
- 2021
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In: International Journal of Cancer. - : John Wiley & Sons. - 0020-7136 .- 1097-0215. ; 150:5, s. 868-880
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Journal article (peer-reviewed)abstract
- Surgical resection with lymphadenectomy and perioperative chemotherapy is the universal mainstay for curative treatment of gastric cancer (GC) patients with locoregional disease. However, GC survival remains asymmetric in West- and East-world regions. We hypothesize that this asymmetry derives from differential clinical management. Therefore, we collected chemo-naïve GC patients from Portugal and South Korea to explore specific immunophenotypic profiles related to disease aggressiveness and clinicopathological factors potentially explaining associated overall survival (OS) differences. Clinicopathological and survival data were collected from chemo-naïve surgical cohorts from Portugal (West-Europe cohort [WE-C]; n = 170) and South Korea (East-Asia cohort [EA-C]; n = 367) and correlated with immunohistochemical expression profiles of E-cadherin and CD44v6 obtained from consecutive tissue microarrays sections. Survival analysis revealed a subset of 12.4% of WE-C patients, whose tumors concomitantly express E-cadherin_abnormal and CD44v6_very high, displaying extremely poor OS, even at TNM stages I and II. These WE-C stage-I and -II patients tumors were particularly aggressive compared to all others, invading deeper into the gastric wall (P = .032) and more often permeating the vasculature (P = .018) and nerves (P = .009). A similar immunophenotypic profile was found in 11.9% of EA-C patients, but unrelated to survival. Tumours, from stage-I and -II EA-C patients, that display both biomarkers, also permeated more lymphatic vessels (P = .003), promoting lymph node (LN) metastasis (P = .019), being diagnosed on average 8 years earlier and submitted to more extensive LN dissection than WE-C. Concomitant E-cadherin_abnormal/CD44v6_very-high expression predicts aggressiveness and poor survival of stage-I and -II GC submitted to conservative lymphadenectomy.
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| 2. |
- Solorzano, Leslie, 1989-, et al.
(author)
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Towards automatic protein co-expression quantification in immunohistochemical TMA slides
- 2021
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In: IEEE journal of biomedical and health informatics. - : Institute of Electrical and Electronics Engineers (IEEE). - 2168-2194 .- 2168-2208. ; 25:2, s. 393-402
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Journal article (peer-reviewed)abstract
- Immunohistochemical (IHC) analysis of tissue biopsies is currently used for clinical screening of solid cancers to assess protein expression. The large amount of image data produced from these tissue samples requires specialized computational pathology methods to perform integrative analysis. Even though proteins are traditionally studied independently, the study of protein co-expression may offer new insights towards patients' clinical and therapeutic decisions. To explore protein co-expression, we constructed a modular image analysis pipeline to spatially align tissue microarray (TMA) image slides, evaluate alignment quality, define tumor regions, and ultimately quantify protein expression, before and after tumor segmentation. The pipeline was built with open-source tools that can manage gigapixel slides. To evaluate the consensus between pathologist and computer, we characterized a cohort of 142 gastric cancer (GC) cases regarding the extent of E-cadherin and CD44v6 expression. We performed IHC analysis in consecutive TMA slides and compared the automated quantification with the pathologists' manual assessment. Our results show that automated quantification within tumor regions improves agreement with the pathologists' classification. A co-expression map was created to identify the cores co-expressing both proteins. The proposed pipeline provides not only computational tools forwarding current pathology practices to explore co-expression, but also a framework for merging data and transferring information in learning-based approaches to pathology.
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