Investigator

Jesús Machuca-Aguado

Facultativo Especialista de Área · Hospital Universitario Virgen Macarena, Pathology Department

JMJesús Machuca-Agu…
Papers(3)
Machine Learning Quan…Correlation between P…From Serous Tubal Int…
Collaborators(2)
Miguel A. IdoateW Glenn McCluggage
Institutions(2)
Hospital Universitari…Belfast Health And So…

Papers

Machine Learning Quantification of Intraepithelial Tumor-Infiltrating Lymphocytes as a Significant Prognostic Factor in High-Grade Serous Ovarian Carcinomas

The prognostic and predictive role of tumor-infiltrating lymphocytes (TILs) has been demonstrated in various neoplasms. The few publications that have addressed this topic in high-grade serous ovarian carcinoma (HGSOC) have approached TIL quantification from a semiquantitative standpoint. Clinical correlation studies, therefore, need to be conducted based on more accurate TIL quantification. We created a machine learning system based on H&E-stained sections using 76 molecularly and clinically well-characterized advanced HGSOC. This system enabled immune cell classification. These immune parameters were subsequently correlated with overall survival (OS) and progression-free survival (PFI). An intense colonization of the tumor cords by TILs was associated with a better prognosis. Moreover, the multivariate analysis showed that the intraephitelial (ie) TILs concentration was an independent and favorable prognostic factor both for OS (p = 0.02) and PFI (p = 0.001). A synergistic effect between complete surgical cytoreduction and high levels of ieTILs was evidenced, both in terms of OS (p = 0.0005) and PFI (p = 0.0008). We consider that digital analysis with machine learning provided a more accurate TIL quantification in HGSOC. It has been demonstrated that ieTILs quantification in H&E-stained slides is an independent prognostic parameter. It is possible that intraepithelial TIL quantification could help identify candidate patients for immunotherapy.

Correlation between P53 immunohistochemical staining and TP53 molecular testing in endometrial carcinomas: a detailed assessment of discrepant cases with implications for patient management

Aims The 2013 Cancer Genome Atlas (TCGA) study identified four molecular types of endometrial carcinoma (EC) that are prognostic and predictive of therapy response. The p53 abnormal (p53abn) group of tumours is associated with aggressive clinical behaviour, chemoresponsiveness and generally high‐grade histology. p53abn tumours may be identified by p53 immunohistochemical staining (a surrogate marker) or molecular testing. In this study, we evaluated the concordance between p53 immunohistochemistry and TP53 molecular testing in a consecutive cohort of ECs from a population‐based setting. Our aim was to investigate the rate of concordance and reasons for discordance between the immunohistochemistry and molecular testing and to provide recommendations for pathologists and clinicians dealing with these discordant cases. Methods and results A total of 386 ECs were included where all biopsy specimens underwent molecular testing using a next‐generation sequencing (NGS) panel (including POLE and TP53 genes and MSI testing) and immunohistochemistry for oestrogen receptor (ER), p53 and mismatch repair (MMR) proteins. Concordance between p53 immunohistochemistry and TP53 NGS was initially 88.6% (discordance of 11.4%) following review of the pathology and molecular reports; most of the discordant cases comprised carcinomas with wild‐type p53 immunohistochemistry but TP53 mutations identified on NGS. The discordance reduced to 6.5% after review of the p53 stained slides, which revealed subclonal mutation‐type staining in some tumours, and to 5% after excluding POLE mutated and mismatch repair deficient carcinomas. However, there remained a small cohort of 19 POLE wild‐type/MMR proficient carcinomas (8 low‐grade endometrioid, 9 high‐grade endometrioid, 2 carcinosarcomas), with wild‐type p53 staining but with TP53 mutations on NGS. Altogether, there were 12 POLE wild‐type/MMR proficient low‐grade endometrioid carcinomas with TP53 mutations on NGS; all were stage I (11 IA, 1 IB). Conclusions Our study demonstrated a good overall concordance between p53 immunohistochemical staining and TP53 molecular results. The concordance can be increased by reviewing the p53 stained slides in discrepant cases but there remains a small cohort of cases, mostly low‐grade endometrioid carcinomas ( POLE wild‐type/MMR proficient), where TP53 mutations are present on NGS but p53 immunohistochemistry is wild‐type. Such cases present a dilemma for the pathologist (which TCGA group should they be placed into) and the clinician (should adjuvant therapy be instigated based on the presence of a TP53 mutation alone with no other adverse features). For now, we advise classifying such cases as p53abn but not to administer adjuvant therapy based on the presence of a TP53 mutation alone without other adverse pathological factors. The significance of TP53 mutations in such cases should be determined by larger studies with long‐term follow‐up.

41Works
3Papers
2Collaborators

Positions

2025–

Facultativo Especialista de Área

Hospital Universitario Virgen Macarena · Pathology Department

2024–

Investigador Postdoctoral

FISEVI

2020–

Trainee

Hospital Universitario Virgen Macarena · Pathology