Towards Personalized Sampling in Clear Cell Renal Cell Carcinomas

Manini, Claudia; López-Fernández, Estíbaliz; López, José I.

doi:10.3390/cancers14143381

Cited by 8 publications

(5 citation statements)

References 28 publications

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“…Concerning CCRCC, it is also crucial to consider the existing high genotypic and phenotypic intratumoral heterogeneity (ITH) [40] when interpreting the divergent results described within non-canonical RAS pathways [26,[34][35][36]. For instance, the antagonistic effects of Ang1-7-Mas signaling could be associated with the use of cell lines and xenograft models derived from distinct tumor cell subpopulations, as suggested by Sobczuk et al [36].…”

Section: Discussionmentioning

confidence: 99%

The Expression of Alamandine Receptor MrgD in Clear Cell Renal Cell Carcinoma Is Associated with a Worse Prognosis and Unfavorable Response to Antiangiogenic Therapy

Larrinaga,

Valdivia,

Arrieta-Aguirre

et al. 2024

IJMS

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Renal cell carcinoma (RCC) ranks among the most prevalent malignancies in Western countries, marked by its notable heterogeneity, which contributes to an unpredictable clinical trajectory. The insufficiency of dependable biomarkers adds complexity to assessing this tumor progression. Imbalances of several components of the intrarenal renin–angiotensin system (iRAS) significantly impact patient prognoses and responses to first-line immunotherapies. In this study, we analyzed the immunohistochemical expression of the Mas-related G-protein-coupled receptor D (MrgD), which recognizes the novel RAS peptide alamandine (ALA), in a series of 87 clear cell renal cell (CCRCCs), 19 papillary (PRCC), 7 chromophobe (ChRCC) renal cell carcinomas, and 11 renal oncocytomas (RO). MrgD was expressed in all the renal tumor subtypes, with a higher mean staining intensity in the PRCCs, ChRCCs, and ROs. A high expression of MrgD at the tumor center and at the infiltrative front of CCRCC tissues was significantly associated with a high histological grade, large tumor diameter, local invasion, and locoregional node and distant metastasis. Patients with worse 5-year cancer-specific survival and a poorer response to antiangiogenic tyrosine-kinase inhibitors (TKIs) showed higher MrgD expression at the center of their primary tumors. These findings suggest a possible role of MrgD in renal carcinogenetic processes. Further studies are necessary to unveil its potential as a novel biomarker for CCRCC prognosis and response to frontline therapies.

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Section: Discussionmentioning

confidence: 99%

The Expression of Alamandine Receptor MrgD in Clear Cell Renal Cell Carcinoma Is Associated with a Worse Prognosis and Unfavorable Response to Antiangiogenic Therapy

Larrinaga,

Valdivia,

Arrieta-Aguirre

et al. 2024

IJMS

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“…It is interesting to note that not only our overall results are in the same range, from 77% to 100%, but also for our study and TCGA validation and biopsy validation for Zhu et al study 17 , most of misclassification concerns ccRCC subgroup. We can assume that this is due to the fact that ccRCC, which is the most frequent tumor subtype, is also known as a tumor composed of clones and sub-clones, conferring intratumor and intertumor heterogeneity, in term of microscopic morphology but also grade, and genetic anomalies [19][20][21] .…”

Section: Discussionmentioning

confidence: 99%

Improving CNNs classification with pathologist-based expertise: the Renal Cell Carcinoma case study

Ponzio

Descombes

2023

Preprint

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The prognosis of renal cell carcinoma (RCC) malignant neoplasms deeply relies on an accurate determination of the histological subtype, which currently involves the light microscopy analysis of histological slides, considering notably tumor architecture and cytology. RCC subtyping is therefore a time-consuming and tedious process, sometimes requiring expert review, with great impact on diagnosis, prognosis and treatment of RCC neoplasms. In this study, we investigate the automatic RCC subtyping classification of 91 patients, diagnosed with clear cell RCC, papillary RCC, chromophobe RCC, or renal oncocytoma, through deep learning based methodologies. We show how the classification performance of several state-of-the-art Convolutional Neural Networks (CNNs) are perfectible among the different RCC subtypes. Thus, we introduce a new classification model leveraging a combination of supervised deep learning models (specifically CNNs) and pathologist’s expertise, giving birth to a hybrid approach that we termed ExpertDeepTree (ExpertDT). Our findings prove ExpertDT’s superior capability in theRCC subtyping task, with respect to traditional CNNs, and suggest that introducing some expert-based knowledge into deep learning models may be a valuable solution for complex classification cases.

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“…While the sequential temporal histological analysis of tumors is not possible in humans, such thorough analyses are perfectly suitable and depend on appropriate specimen handling. Multisite tumor sampling [ 1 , 2 ], for example, guarantees a complete molecular analysis to assure the correct identification of intratumor heterogeneity (ITH) at sustainable costs. ITH is a crucial point in oncological practice because it remains constant in most malignant tumors and is a major cause of therapeutic failure.…”

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confidence: 99%

“…This particular tumor regionalization seems to be a constant event in many tumors. From a practical point of view, this distribution of competencies between tumor center and periphery should guide the needle of radiologists in obtaining tumor tissue at the preoperative stage and the scalpel of pathologists in sampling CCRCC in the grossing room [2] . This new evolutionary perspective, however, needs to be confirmed in larger series.…”

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confidence: 99%