BRAF immunohistochemistry predicts sentinel lymph node involvement in intermediate thickness melanomas

Manninen, Atte; Gardberg, Maria; Juteau, Susanna; Ilmonen, Suvi; Jukonen, Joonas; Andersson, Noora; Carpén, Olli

doi:10.1371/journal.pone.0216043

Cited by 8 publications

(6 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A case-control study of Manninen et al enrolled 140 intermediate-thickness melanoma patients with or without SLN involvement, matched for age, gender, Breslow thickness, and location. They tested the common clinicopathological parameters (ulceration, mitotic count, and tumor regression), BRAF immunoreactivity, and cell motility involving actin-modulating proteins, in relation to SLN involvement and survival [28]. They found a significant correlation between SLN status and BRAF mutation; however, our study did not confirm their findings.…”

Section: Discussioncontrasting

confidence: 86%

Predictive and Prognostic Value of BRAF and NRAS Mutation of 159 Sentinel Lymph Node Cases in Melanoma—A Retrospective Single-Institute Study

Liszkay

Mátrai

Czirbesz

et al. 2021

Cancers

View full text Add to dashboard Cite

Purpose: To assess the prognostic role of sentinel lymph node status (SLN) in melanoma patients, a statistical comparison was performed with the application of already known prognostic factors, mutational occurrence of BRAF and NRAS in the primary tumor, as well as disease outcome. Methods: Our retrospective single-center study involved 159 melanoma cases, who underwent SLN biopsy. The following clinico-pathological data were collected: age, gender, location of primary tumor, Breslow thickness, ulceration degree, histological subtype, mitosis count, lymphovascular and perineural invasion, presence of tumor-infiltrating lymphocytes, regression signs, mutations of BRAF and NRAS of the primary tumors, and SLN status. Results: From the studied clinico-pathological factors, only Breslow thickness increased the risk of SLN positivity (p = 0.025) by multivariate analysis, while neither BRAF nor NRAS mutation of the primary tumor proved to be a predictor of the SLN status. While the NRAS-mutant subgroup showed the most unfavorable outcome for progression-free and distant metastasis-free survival, their rate of positive SLNs proved to be relatively lower than that of patient groups with BRAF mutation and double-wild-type phenotypes. Conclusion: Similarly to the importance of SLN positivity, NRAS mutation of the primary tumor proved to be an independent prognostic factor of progression. Therefore, despite negative SLN, this NRAS-mutant subgroup of patients still requires closer monitoring to detect disease progression.

show abstract

Section: Discussioncontrasting

confidence: 86%

Predictive and Prognostic Value of BRAF and NRAS Mutation of 159 Sentinel Lymph Node Cases in Melanoma—A Retrospective Single-Institute Study

Liszkay

Mátrai

Czirbesz

et al. 2021

Cancers

View full text Add to dashboard Cite

show abstract

“…In this research, we drove several scripts as a bioinformatic visualization and calculation of the clinical samples and tissue optical feature as it had been linked to FMNLs in BrCa access to online databases which contains large cohort and high credibility, evaluating the prognostic value of FMNL expression level in the treatment strategies of breast cancer [ 10 ]. Overall, our research preliminarily but systematically characterized the expression profiles of FMNLs in BrCa and revealed that the detection of the FMNL expression status of BrC patients may be valuable and potential biomarkers for prognostic assessment.…”

Section: Introductionmentioning

confidence: 99%

Systematic Characterization of Expression Patterns and Immunocorrelations of Formin-Like Genes in Breast Cancer

Gao

Wang

et al. 2022

BioMed Research International

View full text Add to dashboard Cite

Background. Members of the formin-like gene (FMNL) family are required for cytoskeleton-related processes, and their expressions are implicated to the progression of a multitude of malignancies. However, there are insufficient studies on transcription factors and promising prognosis benefit of FMNLs during the genesis of breast cancer (BrCa). Methods. The transcriptional levels of FMNL family members in primary BrCa tissues and their association with intrinsic subclasses were analyzed using the UALCAN database. Then, the prognostic values of FMNLs in BrCa patients were investigated via the Kaplan-Meier plotter. Moreover, the correlations between FMNL expression levels and immune infiltrations were analyzed using the TIMER database. In addition, the expression patterns of FMNLs in BrCa were investigated by single-cell RNA-sequencing (scRNA-seq) analysis and were validated by immunohistochemistry (IHC) staining. Results. The transcriptional level of FMNL1 was shown to be considerably increased in BrCa. It is surprising that the transcriptional quantities of FMNL2 and FMNL3 were substantially reduced. In addition, during the comparison of several BrCa subclasses, FMNL1 and FMNL2 mRNA levels of patients with HER2-positive and triple-negative BrCa subclasses increased, while FMNL3 mRNA levels reduced. With the processions of experimentation, high FMNL1 expression was hopefully linked to well clinical outcome, while high FMNL2 expression predicted poor prognosis. Moreover, FMNL1 was highly expressed in tumor-infiltrating immune cells (TIICs) in tumor tissues. Last but not least, FMNL1 was highly expressed in TIICs and served as a gene marker for TIICs. Conclusions. The fact and result which we analyzed demonstrate FMNL1 as a diagnostic marker for TIICs by comprehensively elucidating the expression patterns and changeable prognostic implications of FMNLs in BrCa clinical applications.

show abstract

“…Younger age, mitotic rate, and the level of tumour-infiltrating lymphocytes may also influence SLN status [13,14]. BRAF mutations may be correlated with SLN positivity [15]. Expression analysis of isolated markers or of marker combinations may also contribute to predicting lymphatic metastases [16e18] and in addition may identify those patients that will relapse in spite of a negative SN biopsy and therefore can be identified as candidate for adjuvant therapy [19].…”

Section: Introductionmentioning

confidence: 99%

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours

Brinker

Kiehl

Schmitt

et al. 2021

European Journal of Cancer

View full text Add to dashboard Cite

Sentinel lymph node status is a central prognostic factor for melanomas. However, the surgical excision involves some risks for affected patients. In this study, we therefore aimed to develop a digital biomarker that can predict lymph node metastasis noninvasively from digitised H&E slides of primary melanoma tumours. Methods: A total of 415 H&E slides from primary melanoma tumours with known sentinel node (SN) status from three German university hospitals and one private pathological practice were digitised (150 SN positive/265 SN negative). Two hundred ninety-one slides were used to train artificial neural networks (ANNs). The remaining 124 slides were used to test the ability of the ANNs to predict sentinel status. ANNs were trained and/or tested on data sets that were matched or not matched between SN-positive and SN-negative cases for patient age, ulceration, and tumour thickness, factors that are known to correlate with lymph node status. Results: The best accuracy was achieved by an ANN that was trained and tested on unmatched cases (61.8% AE 0.2%) area under the receiver operating characteristic (AUROC). In contrast, ANNs that were trained and/or tested on matched cases achieved (55.0% AE 3.5%) AUROC or less. Conclusion:Our results indicate that the image classifier can predict lymph node status to some, albeit so far not clinically relevant, extent. It may do so by mostly detecting equivalents of factors on histological slides that are already known to correlate with lymph node status. Our results provide a basis for future research with larger data cohorts.

show abstract

BRAF immunohistochemistry predicts sentinel lymph node involvement in intermediate thickness melanomas

Cited by 8 publications

References 24 publications

Predictive and Prognostic Value of BRAF and NRAS Mutation of 159 Sentinel Lymph Node Cases in Melanoma—A Retrospective Single-Institute Study

Predictive and Prognostic Value of BRAF and NRAS Mutation of 159 Sentinel Lymph Node Cases in Melanoma—A Retrospective Single-Institute Study

Systematic Characterization of Expression Patterns and Immunocorrelations of Formin-Like Genes in Breast Cancer

Deep learning approach to predict sentinel lymph node status directly from routine histology of primary melanoma tumours

Contact Info

Product

Resources

About