BRAF immunohistochemistry predicts sentinel lymph node involvement in intermediate thickness melanomas

Tissue Biomarkers Predicting Lymph Node Status in Cutaneous Melanoma

Cutaneous melanoma is a severe neoplasm that shows early invasiveness of the lymph nodes draining the primary site, with increased risk of distant metastases and recurrence. The tissue biomarker identification could be a new frontier to predict the risk of early lymph node invasiveness, especially in cases considered by current guidelines to be at low risk of lymph node involvement and not requiring evaluation of the sentinel lymph node (SLN). For this reason, we present a narrative review of the literature, seeking to provide an overview of current tissue biomarkers, particularly vascular endothelium growth factors (VEGF), Tetraspanin CD9, lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1), D2-40, and gene expression profile test (31-GEP). Among these, 31-GEP seems to be able to provide a distinction between low or high risk for positive SLN classes. VEGF receptor-3 and CD9 expression may be independent predictors of positive SLN. Lastly, LYVE-1 and D2-40 allow an easier assessment of lymph vascular invasion, which can be considered a good predictor of SLN status. In conclusion, biomarkers to assess the lymph node status of cutaneous melanoma patients may play an important role in those cases where the clinician is in doubt whether or not to perform SLN biopsy.

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

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.

[Immunohistochemical analysis of a hypoxia-associated signature in melanomas with positive and negative sentinel lymph nodes : Hypoxia-associated signature of primary cutaneous melanomas]

Metabolic reprogramming mediated by hypoxia-inducible factors and its downstream targets plays a crucial role in many human malignancies. Excessive proliferation of tumor cells under hypoxic conditions leads to metabolic reprogramming and altered gene expression enabling tumors to adapt to their hypoxic environment. Here we analyzed the metabolic signatures of primary cutaneous melanomas with positive and negative sentinel node status in order to evaluate potential differences in their metabolic signature. We found a positive correlation of the expression of glucose transporter 1 (GLUT-1) with tumor thickness and ulceration in all melanomas with subgroup analyses as well as in the subgroup with a negative sentinel node. Furthermore, the expression of vascular endothelial growth factor (VEGF) was positively correlated with the presence of ulceration in melanomas with positive sentinel node.

Changing Trends in Dermatopathology Case Complexity: A 9-Year Academic Center Experience

CONTEXT.—

Pathology case volume and complexity impact clinical service burden, staffing, and reimbursement, particularly in an academic setting.

OBJECTIVE.—

To investigate dermatopathology case complexity by using indicators of challenging cases, which require increased clinical service effort.

DESIGN.—

A retrospective review was performed of dermatopathology cases during a 9-year period at a tertiary care academic center. A subset of cases was analyzed for which extractable data were available. Cases requiring the following metrics of complexity were identified: rush processing, consensus agreement, performance of immunohistochemistry, use of special histochemical stains, use of immunofluorescence, examination of additional tissue levels, review of a prior case, addition of an explanatory note, presence of multiple specimen parts, and use of intradepartmental consultation.

RESULTS.—

A total of 8173 cases were reviewed. During the same 3-month period of the year, there was a statistically significant increase in use of rush processing/interpretation, consensus review, number of cases requiring immunostains, special stains, levels, and an explanatory note, and cases reviewed by other subspecialists in the department from 2010 to 2019.

CONCLUSIONS.—

This study shows an increasing trend in dermatopathology case complexity, suggesting that overall clinical service efforts have increased. These findings may inform clinical service staffing and reimbursement.

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

AIM

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 non-invasively 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% ± 0.2%) area under the receiver operating characteristic (AUROC). In contrast, ANNs that were trained and/or tested on matched cases achieved (55.0% ± 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.

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

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.

Pathology-based Biomarkers Useful for Clinical Decisions in Melanoma

The dramatic recent advances in therapy of melanoma require a more personalized and precise diagnostic approach to aid in clinical decisions. Tissue-based biomarkers in pathology have diagnostic, prognostic and predictive relevance. Herein we review the most commonly used pathology-based biomarkers in melanoma. Most of these biomarkers are evaluated through immunohistochemistry (IHC) or fluorescent in situ hybridization (FISH) performed on formalin fixed paraffin embedded tissue (FFPE), and are widely available in clinical pathology laboratories. We describe the utility of MART1/Ki67, p16, PRAME, markers of lymphovascular invasion (D2-40, CD31, D2-40/MITF, CD31/SOX-10), BRAF V600E, NRAS, KIT, BAP1, ALK, NTRK, PD-L1, TERT, PTEN, iNOS, and MMR proteins (MLH1, MSH2, MSH6, PMS2) in the evaluation of melanoma specimens. Correct interpretation and awareness of the significance of these biomarkers is crucial for pathologists, dermatologists, and oncologists who take care of melanoma patients.