Update on Prostate Cancer Diagnosis, Prognosis, and Prediction to Response to Therapy

Montironi, Rodolfo; Cimadamore, Alessia; López-Beltrán, Antonio; Cheng, Liang; Scarpelli, Marina

doi:10.3390/cells10010020

Cited by 7 publications

(6 citation statements)

References 18 publications

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“…However, it is worth mentioning a proposal made in the late 1990s in an invited lecture at the Milan (Italy) National Cancer Institute, in a seminar organized by the late Dr Juan Rosai. The proposal was in favor of a classification of the preinvasive lesions of the prostate based on an approach similar to that in the breast and taking into consideration what was reported in the 1987 Dr Bostwick’s publication of the concept of “Grade 3, representing carcinoma in situ”: 1 low nuclear grade (ie, LGPIN), intermediate nuclear grade (ie, HGPIN) and high nuclear grade (ie, IDC-P). The comment made by Dr Rosai was a laconic one as if not endorsing it.…”

Section: The Real Beginning Of Our Experience With Prostate Neoplasmsmentioning

confidence: 99%

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Histopathology of Prostate Cancer and its Precursors

Montironi

Cimadamore

Mazzucchelli

et al. 2022

Applied Immunohistochemistry &Amp; Molecular Morphology

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Starting in the mid-1970s, we formed a group of pathologists with a major interest in uropathology. Originally, it included 2 (R.M. and M.S.). In the years the followed, the group was enlarged to include 4 more people, 2 in the mid- and late-1980s (A.L.B. and L.C.) and another in the mid-1990s (R.Ma.); a sixth (A.C.) joined the group ∼5 years ago. Two have reached the retirement age (R.M. and M.S.), while others are in the process of joining the group to replace them. A fruitful collaboration spanned for ∼45 years. This contribution is based on a series of personal recollections of the successive changes in the interpretation of prostate cancer and its precursors, starting in the mid-1970s. Here we have retraced our involvement steps, sharing issues related to them with a junior uropathologist (A.C.).

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Section: The Real Beginning Of Our Experience With Prostate Neoplasmsmentioning

confidence: 99%

“…Such specimens have allowed us to acquire deep knowledge of the morphology of the lesions and of their spectrum and, above all, of their clinical significance. This was always coupled with an active research activity 1 …”

mentioning

confidence: 99%

Histopathology of Prostate Cancer and its Precursors

Montironi

Cimadamore

Mazzucchelli

et al. 2022

Applied Immunohistochemistry &Amp; Molecular Morphology

Self Cite

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“…Today, the healthcare system has benefited greatly from a number of advantages of artificial intelligence (AI)‐based strategies, such as the chance of storing, comparing, and classifying enormous data via high‐speed computers, and all these fashions have been precisely implemented into the fields of drug delivery, medicine, and cancer research (treatment, imaging, and cell sorting). [ 178–183 ] In particular, machine learning (ML)—an application of AI—enables automatically learning of the trained datasets without any internal programming. The attribution of recognizing and analyzing patterns employed in biomedical and clinical areas creates an enormous level of heterogeneous data.…”

Section: Artificial Intelligence Of Cell Isolation and Characterizationmentioning

confidence: 99%

Smart Material‐Integrated Systems for Isolation and Profiling of Rare Cancer Cells and Emboli

Sagdic

İnci

2021

Adv Eng Mater

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This review presents a broad aspect of smart material‐integrated systems for isolating and profiling rare circulating tumor cells (CTCs) and circulating tumor microemboli (CTM) to provide physiological, biological, and mechanistic insights into cancer research. In particular, CTCs/CTM have emanated as essential pieces of evidence that can reveal clonal evolution, tumor heterogeneity, and disease progression within the metastatic cascade. Morphologies, cellular compositions, and rarity of CTCs/CTM make them difficult to track and isolate for profiling distinct molecular characteristics in the case of metastatic potential. Accordingly, with the advanced‐characterization techniques, examining the aspects of the specific surface markers of CTCs/CTM, epithelial‐to‐mesenchymal (EMT), mesenchymal‐to‐epithelial (MET) transitions, and timing of tumor cell dissemination would assist us to understand cancer biology and metastatic characteristics. Existing clinical and research methods for the enrichment and isolation of these sporadic cells depend on mainly conventional methods with low‐yield and expensive features. Owing to their specialized functions and analytical performances, smart material‐based technologies hold an enormous impact not only on cell detection, but also on cell isolation for downstream analyses. Herein, the main reasons for cell isolation are discussed and the recent developments in CTCs/CTM approaches for identifying further methods and future perspectives are elaborated on.

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“…Prostate cancer (PCa) is the most commonly diagnosed cancer and the second leading cause of cancer‐related death among men 1,2 . Appropriate treatment requires accurate prognostic prediction 3 . However, numerous studies have demonstrated that currently used prognostic indicators, including prostate‐specific antigen (PSA) level, clinical stage and Gleason grade, inadequately predict the prognosis of PCa patients, particularly men with clinically localized disease 4–6 .…”

Section: Introductionmentioning

confidence: 99%

A glycosylation signature for predicting the progression and immunotherapeutic response of prostate cancer

Sun

Fan

Min

et al. 2023

The Journal of Gene Medicine

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Background Glycosylation has been proposed as a new cancer hallmark. However, focusing on specific glycans or glycoproteins may lose much data relevant to glycosylation alterations. The present study aimed to first comprehensively investigate the expression and mutation profiles of glycosylation‐related genes (GRgenes) in prostate cancer (PCa) and then develop a glycosylation signature and explore its role in predicting the progression and immunotherapeutic response of PCa. Methods Based on The Cancer Genome Atlas database, we comprehensively screened potential prognostic GRgenes and analyzed their expression and mutation profiles in PCa. Through consensus clustering analysis, the study cohort was classified to investigate the effect of glycosylation patterns on the prognosis of PCa. Next, we developed a glycosylation signature (i.e., the glycosylation score [Gly_score]) using the differentially expressed genes between glycosylation pattern groups and evaluated its role in predicting the progression and immunotherapeutic response of PCa. Results We identified two distinct glycosylation patterns in PCa and found that GRgene expression patterns rather than mutations are associated with the prognosis of PCa. The high Gly_score group had significantly shorter progression‐free survival, lower PD‐L1 levels, less infiltration of immune cells and lower immunophenoscores than the low Gly_score group. When the patients were grouped according to both the Gly_score and PD‐L1 level, patients with a combination of low Gly_score and low PD‐L1 expression had the best survival outcomes. Conclusions In the present study, for the first time, we developed a glycosylation signature and demonstrated that the proposed glycosylation signature is a promising tool for predicting the prognosis and immunotherapeutic response of PCa.

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Update on Prostate Cancer Diagnosis, Prognosis, and Prediction to Response to Therapy

Cited by 7 publications

References 18 publications

Histopathology of Prostate Cancer and its Precursors

Histopathology of Prostate Cancer and its Precursors

Smart Material‐Integrated Systems for Isolation and Profiling of Rare Cancer Cells and Emboli

A glycosylation signature for predicting the progression and immunotherapeutic response of prostate cancer

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