Immunohistochemistry as a Practical Tool in Molecular Pathology

Clinical retrospective analysis with a predictive model for diffused-tenosynovial giant cell tumors of the temporomandibular joint

BACKGROUND

This study aimed to find out the characteristics in relation to tumor recurrence in diffused-tenosynovial giant cell tumor of temporomandibular joint and to develop and validate the prognostic model for personalized prediction.

METHODS

From April 2009 to January 2021, patients with diffused-tenosynovial giant cell tumor of temporomandibular joint at a single center were included in this study. The clinical features and local recurrence-free survival were assessed through the expression of the Ki-67 index and colony-stimulating factor 1 receptor expression. Both univariate and multivariate analyses were performed on the prognostic factors for local recurrence-free survival. An independent predictor nomogram and pertinent tumor characteristics were included.

RESULTS

The retrospective study enrolling seventy eligible patients at the Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine. During the follow-up time, eleven patients suffered tumor recurrence. Age was an independent risk factor for local recurrence-free survival (P = 0.032). The Ki-67 index varied significantly in different sites (P = 0.034) and tumor volume (P = 0.017). Multivariate logistic regression was used to develop the prediction model using both statistical significance and prognostic indicators. The C-index of the nomogram based on age, site, Ki-67, and colony-stimulating factor 1 receptor was 0.833. These variates provided good predicted accuracy for a nomogram on local recurrence-free survival. Diffused-tenosynovial giant cell tumor from the temporomandibular joint is extremely uncommon, and certain clinical traits are linked to the tumor proliferation index.

CONCLUSIONS

We identified the risk indicators and developed a nomogram in this study to forecast the likelihood of local recurrence-free survival in patients with diffused-tenosynovial giant cell tumor from temporomandibular joint.

Prognostic Value of BAP1 and Preferentially Expressed Antigen in Melanoma (PRAME) Immunohistochemistry in Uveal Melanomas

Uveal melanoma (UM) is the most common primary intraocular tumor in adults, and despite excellent local control, more than 50% of patients develop and die from metastatic disease. Loss of BAP1 nuclear staining, a surrogate marker of BAP1 mutation, and preferentially expressed antigen in melanoma (PRAME) messenger RNA overexpression, as assessed using qPCR, have previously been shown to correlate with increased metastasis rate in UM. In this study, we demonstrated that UM could be successfully risk-stratified using a combination of BAP1 and PRAME immunohistochemical (IHC) stains. We retrospectively reviewed 318 UM cases with sufficient tissue and performed BAP1 and PRAME IHC to stratify them as BAP1+/PRAME- (group 1, n = 135), BAP1+/PRAME+ (group 2, n = 43), BAP1-/PRAME- (group 3, n = 94), and BAP1-/PRAME+ (group 4, n = 46). Increasing the study risk group on the basis of loss of BAP1 expression and positive PRAME staining was associated with a higher rate of metastasis and disease-specific death and lower metastasis-free survival (MFS) and disease-specific survival (DSS). Among tumors with loss of BAP1 staining, PRAME positivity was associated with shorter MFS (P = .018) and showed a trend toward shorter DSS (P = .061). Among tumors with retained BAP1 staining, PRAME positivity was associated with shorter MFS and DSS (P = .001 and P = .021, respectively). In summary, a combination of BAP1 and PRAME IHC can be used for risk stratification of UMs.

Therapeutically Targeting Cancers That Overexpress FOXC1: A Transcriptional Driver of Cell Plasticity, Partial EMT, and Cancer Metastasis

Metastasis accounts for more than 90% of cancer related mortality, thus the most pressing need in the field of oncology today is the ability to accurately predict future onset of metastatic disease, ideally at the time of initial diagnosis. As opposed to current practice, what would be desirable is that prognostic, biomarker-based detection of metastatic propensity and heightened risk of cancer recurrence be performed long before overt metastasis has set in. Without such timely information it will be impossible to formulate a rational therapeutic treatment plan to favorably alter the trajectory of disease progression. In order to help inform rational selection of targeted therapeutics, any recurrence/metastasis risk prediction strategy must occur with the paired identification of novel prognostic biomarkers and their underlying molecular regulatory mechanisms that help drive cancer recurrence/metastasis (i.e. recurrence biomarkers). Traditional clinical factors alone (such as TNM staging criteria) are no longer adequately prognostic for this purpose in the current molecular era. FOXC1 is a pivotal transcription factor that has been functionally implicated to drive cancer metastasis and has been demonstrated to be an independent predictor of heightened metastatic risk, at the time of initial diagnosis. In this review, we present our viewpoints on the master regulatory role that FOXC1 plays in mediating cancer stem cell traits that include cellular plasticity, partial EMT, treatment resistance, cancer invasion and cancer migration during cancer progression and metastasis. We also highlight potential therapeutic strategies to target cancers that are, or have evolved to become, “transcriptionally addicted” to FOXC1. The potential role of FOXC1 expression status in predicting the efficacy of these identified therapeutic approaches merits evaluation in clinical trials.

Challenges and Opportunities in the Statistical Analysis of Multiplex Immunofluorescence Data

Simple Summary

Immune modulation is considered a hallmark of cancer initiation and progression, and has offered promising opportunities for therapeutic manipulation. Multiplex immunofluorescence (mIF) technology has enabled the tumor immune microenvironment (TIME) to be studied at an increased scale, in terms of both the number of markers and the number of samples. Another benefit of mIF technology is the ability to measure not only the abundance but also the spatial location of multiple cells types within a tissue sample simultaneously, allowing for assessment of the co-localization of different types of immune markers. Thus, the use of mIF technologies have enable researchers to characterize patient, clinical, and tumor characteristics in the hope of identifying patients whom might benefit from immunotherapy treatments. In this review we outline some of the challenges and opportunities in the statistical analyses of mIF data to study the TIME.

Abstract

Immune modulation is considered a hallmark of cancer initiation and progression. The recent development of immunotherapies has ushered in a new era of cancer treatment. These therapeutics have led to revolutionary breakthroughs; however, the efficacy of immunotherapy has been modest and is often restricted to a subset of patients. Hence, identification of which cancer patients will benefit from immunotherapy is essential. Multiplex immunofluorescence (mIF) microscopy allows for the assessment and visualization of the tumor immune microenvironment (TIME). The data output following image and machine learning analyses for cell segmenting and phenotyping consists of the following information for each tumor sample: the number of positive cells for each marker and phenotype(s) of interest, number of total cells, percent of positive cells for each marker, and spatial locations for all measured cells. There are many challenges in the analysis of mIF data, including many tissue samples with zero positive cells or “zero-inflated” data, repeated measurements from multiple TMA cores or tissue slides per subject, and spatial analyses to determine the level of clustering and co-localization between the cell types in the TIME. In this review paper, we will discuss the challenges in the statistical analysis of mIF data and opportunities for further research.

Molecular profiling of the intestinal mucosa and immune cells of the colon by multi-parametric histological techniques

The impact of the post-mortem interval (PMI) on the optical molecular characteristics of the colonic mucosa and the gut-associated lymphoid tissue (GALT) were examined by multi-parametric measurements techniques. Inflammatory cells were identified by immunohistochemical staining. Molecular parameters were estimated using the Raman spectroscopy (RS) and Fourier Transform Infrared (FTIR) spectroscopic imaging. The 3D refractive index (3D-RI) distributions of samples were determined using the digital holographic tomography. The distribution of immune cells between post-mortem (PM) and normal controls did show significant differences for CD4 (P = 0.0016) or CD8 (P < 0.0001), whose expression level was decreased in PM cases. No association was found between individual PMI values and inflammatory cell distribution. However, there was a tendency for a negative correlation between CD4⁺ cells and PMI (r = - 0.542, P = 0.032). The alterations ongoing in post-mortem tissue may suggest that PMI has a suppressive effect on the effector properties of the cell-mediated immunity. Moreover, it was confirmed that spectroscopic and digital holotomographic histology are also a useful technique for characterization of the differences in inflammation of varying intensity and in GALT imaging in a solid tissue. Anatomical location of immune cells and methods of tissue fixation determine the molecular and optical parameters of the examined cases.

Comprehensive pathological assessment of histological subtypes, molecular subtypes based on immunohistochemistry, and tumor-associated immune cell status in muscle-invasive bladder cancer

Molecular assessments of muscle-invasive bladder cancer (MIBC) have yielded several molecular categorizations associated with basal and luminal subtypes or tumor-associated immune cell status (TAICs). However, the histological relationships among histological subtypes, molecular subtypes, and TAICs and their clinical implications remain unclear. Thus, we aimed to evaluate the histological associations among these factors and their clinicopathological outcomes. We retrospectively analyzed 106 patients with MIBC who underwent radical cystectomy. The histological subtypes and TAICs were evaluated with hematoxylin and eosin staining, while the basal and luminal molecular subtypes were determined by immunohistochemical expression of cytokeratin (CK) 5/6, CK14, CK20, GATA3 and uroplakin II. Urothelial carcinoma with squamous differentiation and the sarcomatoid variant were highly associated with the basal subtype (P < 0.001 and P = 0.04, respectively). Additionally, high TAICs were significantly correlated with the basal subtype (P < 0.001). Although there was no significant difference in the cancer-specific survival (CSS) rate between molecular subtypes (P = 0.295), TAICs significantly discriminated CSS rates (P < 0.001). Furthermore, the combination of molecular subtypes and TAICs significantly stratified cancer-specific mortality rates. In conclusion, a comprehensive pathological evaluation of histological subtypes, molecular subtypes, and TAICs is feasible and can influence the oncological outcome.

Impact of CD144 gene expression on outcomes in stage III gastric cancer patients

CD144 has been shown to promote tumour angiogenesis, invasion and metastasis in malignant tumours. The purpose of the present study was to investigate the clinical prognostic significance of CD144 in advanced gastric cancer (GC) to complement the American Joint Committee on Cancer (AJCC) 8th Edition convention. We established that CD144 was highly related to angiogenesis using The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) public databases. We randomly selected 173 stage III GC patients who received curative gastrectomy. The expression level of CD144 was assessed by immunohistochemistry and Image-Pro Plus software. After survival analysis, nomograms were created to predict the risk of stage III gastric cancer patients' 5-years survival. In this study, the median value of the CD144 positive area/total area under the microscope was 5.6%, and this was defined as the cut-off value. The expression of CD144 assisted further subgrouping of stage Ⅲa, Ⅲb, and Ⅲc GC patients. To evaluate the disease-free survival (DFS) and overall survival (OS) of patients, univariate and multivariate analysis was performed, which showed that the expression of CD144 was an independent predictor for DFS, and Borrmann type and expression of CD144 were independent predictors for OS (p<0.05). Nomograms were used to evaluate the risk of stage III GC by combining Borrmann type and the expression level of CD144. In advanced GC patients, the expression level of CD144 is a useful prognostic indicator in evaluating the risk of disease prognosis.

Clinicopathological study of ameloblastoma and detection of human papilloma virus by immunohistochemistry

Objective:

To study the clinocopathological factors and presence of Human Pappiloma Virus in ameloblastoma by immnohistochemistry.

Methods:

It was a cross sectional study on 50 surgical specimens of ameloblastoma, completed in six months. These were selected and processed for initial screening by H&E and then by immunohistochemistry (IHC) for detection of Human Papilloma Virus (HPV). The questionnaire was designed to study the clinicopathological factors associated in these patients. Sections of 4µm were cut, placed on special positive charged glass slides in the Department of Pathology, King Edward Medical University. It was then examined by the histopathologists for grading and scoring of these lesions. Chi Square test was used to assess the differences found in types of ameloblastomas. The p-value was smaller than 0.05 (p < 0.05).

Results:

The mean age of the patients (12-80 years old) was 38.6±15.1 years, with male-female ratio 2.84: 1. HPV was positive in 9 (18%), whereas negative in of 41 (82%) patients. Among the positive, reactive HPV with score-1 was 8 and score-2 was 1. According to histological variant, follicular was present in 78%, Plexiform pattern in 8%, Conventional and Desmoplastic variants in one patient each; and Cystic and Acanthomatous were seen in two and three patients respectively. The mandible was involved in 39 patients, maxilla and right maxilla involved in 4 patients each, right retromolar, cheek and angle of mandible was seen in one patient each. About 16% patients had anterior, 66% had posterior and 18% had both anterior and posterior regions involved. Among the HPV positive reactive statistically, no significant difference was found with smoking, Paan and exposure to pesticides, factory or mine (p-value > 0.05). Among HPV positive reactive patients, eight had ameloblastoma whereas, 1 had ameloblastomic fibroma. There was no statistical significance of type, location and region of tumor in HPV positivity.

Conclusion:

Mandible and posterior region was more commonly involved. Follicular pattern was most common. There was no effect of exposure to pesticides, factory or mine, smoke and human papilloma virus in the etiology of ameloblastoma because only 18% of patients showed the association of HPV16

A novel protein-based prognostic signature improves risk stratification to guide clinical management in early-stage lung adenocarcinoma patients

Each of the pathological stages (I-IIIa) of surgically resected non-small-cell lung cancer has hidden biological heterogeneity, manifested as heterogeneous outcomes within each stage. Thus, the finding of robust and precise molecular classifiers with which to assess individual patient risk is an unmet medical need. Here, we identified and validated the clinical utility of a new prognostic signature based on three proteins (BRCA1, QKI, and SLC2A1) to stratify early-stage lung adenocarcinoma patients according to their risk of recurrence or death. Patients were staged according to the new International Association for the Study of Lung Cancer (IASLC) staging criteria (8th edition, 2018). A test cohort (n = 239) was used to assess the value of this new prognostic index (PI) based on the three proteins. The prognostic signature was developed by Cox regression with the use of stringent statistical criteria (TRIPOD: Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis). The model resulted in a highly significant predictor of 5-year outcome for disease-free survival (p < 0.001) and overall survival (p < 0.001). The prognostic ability of the model was externally validated in an independent multi-institutional cohort of patients (n = 114, p = 0.021). We also demonstrated that this molecular classifier adds relevant information to the gold standard TNM-based pathological staging, with a highly significant improvement of the likelihood ratio. We subsequently developed a combined PI including both the molecular and the pathological data that improved the risk stratification in both cohorts (p ≤ 0.001). Moreover, the signature may help to select stage I-IIA patients who might benefit from adjuvant chemotherapy. In summary, this protein-based signature accurately identifies those patients with a high risk of recurrence and death, and adds further prognostic information to the TNM-based clinical staging, even when the new IASLC 8th edition staging criteria are applied. More importantly, it may be a valuable tool for selecting patients for adjuvant therapy. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.