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Curative lung resection remains the key therapeutic strategy for early-stage non–small cell lung cancer (NSCLC). However, a proportion of patients still experience variable outcomes and eventually develop recurrence or die from their disease. Proprotein convertase subtilisin/kexin type 9 (PCSK9) has been identified as a deleterious factor that inhibits tumor cells apoptosis and leads to reduction of lymphocyte infiltration. However, there has been no research on the predicted role of PCSK9 as an immunohistochemical biomarker with survival in resectable NSCLC. One hundred sixty-three patients with resectable NSCLC were retrospectively reviewed, and PCSK9 expression of resected NSCLC was analyzed by immunohistochemistry using tissue microarrays. PCSK9 was associated with recurrence (42.1% relapsed in the PCSK9lo group versus 57.9% relapsed in the PCSK9hi group, P = 0.006) and survival status (39.6% dead in PCSK9lo group versus 60.4% dead in PCSK9hi group, P = 0.004) in patients with resectable NSCLC. Moreover, resectable NSCLC patients with higher PCSK9 expression in tumor tissue experienced poorer disease-free survival (median disease-free survival: 10.5 versus 25.2 mo, hazard ratio = 1.620, 95% confidence interval: 1.124-2.334) and overall suvrival (median overall suvrival: 20.0 versus 54.1 mo, hazard ratio = 1.646, 95% confidence interval: 1.101-2.461) compared to those with lower PCSK9 expression. High PCSK9 expression of tumor was correlated with recurrence and worse survival status of resectable NSCLC in our retrospective study, which indicated that PCSK9 in NSCLC may be an immunohistochemical biomarker of poor prognosis for patients with resectable NSCLC. Further large-scale prospective studies are warranted to establish these results. • Proprotein convertase subtilisin/kexin type 9 (PCSK9) affects various tumor cell processes and immune cells infiltration. • Real-world research of PCSK9 was needed in treatment of resectable non–small cell lung cancer (NSCLC). • Retrospective study addresses the predict role of PCSK9 on resectable NSCLC prognosis. • Patients with high expression of PCSK9 in resected NSCLC experience poor overall and disease-free survival. [ABSTRACT FROM AUTHOR]

Gliomas are primary brain tumors that arise from neural stem cells, or glial precursors. Diagnosis of glioma is based on histological evaluation of pathological cell features and molecular markers. Gliomas are infiltrated by myeloid cells that accumulate preferentially in malignant tumors, and their abundance inversely correlates with survival, which is of interest for cancer immunotherapies. To avoid time-consuming and laborious manual examination of images, a deep learning approach for automatic multiclass classification of tumor grades was proposed. As an alternative way of investigating characteristics of brain tumor grades, we implemented a protocol for learning, discovering, and quantifying tumor microenvironment elements on our glioma dataset. Using only single-stained biopsies we derived characteristic differentiating tumor microenvironment phenotypic neighborhoods. The study was complicated by the small size of the available human leukocyte antigen stained on glioma tissue microarray dataset — 206 images of 5 classes — as well as imbalanced data distribution. This challenge was addressed by image augmentation for underrepresented classes. In practice, we considered two scenarios, a whole slide supervised learning classification, and an unsupervised cell-to-cell analysis looking for patterns of the microenvironment. In the supervised learning investigation, we evaluated 6 distinct model architectures. Experiments revealed that a DenseNet121 architecture surpasses the baseline's accuracy by a significant margin of 9% for the test set, achieving a score of 69%, increasing accuracy in discerning challenging WHO grade 2 and 3 cases. All experiments have been carried out in a cross-validation manner. The tumor microenvironment analysis suggested an important role for myeloid cells and their accumulation in the context of characterizing glioma grades. Those promising approaches can be used as an additional diagnostic tool to improve assessment during intraoperative examination or subtyping tissues for treatment selection, potentially easing the workflow of pathologists and oncologists. [ABSTRACT FROM AUTHOR]

Whilst automated analysis of immunostains in pathology research has focused predominantly on the epithelial compartment, automated analysis of stains in the stromal compartment is challenging and therefore requires time-consuming pathological input and guidance to adjust to tissue morphometry as perceived by pathologists. This study aimed to develop a robust method to automate stromal stain analyses using 2 of the commonest stromal stains (SMA and desmin) employed in clinical pathology practice as examples. An effective computational method capable of automatically assessing and quantifying tumour-associated stromal stains was developed and applied on cores of colorectal cancer tissue microarrays. The methodology combines both mathematical models and deep learning techniques with the former requiring no training data and the latter as many inputs as possible. The novel mathematical model was used to produce a digital double marker overlay allowing for fast automated digital multiplex analysis of stromal stains. The results show that deep learning methodologies in combination with mathematical modelling allow for an accurate means of quantifying stromal stains whilst also opening up new possibilities of digital multiplex analyses.

Huntington's disease (HD) is a neurodegenerative disorder that severely affects the basal ganglia and regions of the cerebral cortex. While astrocytosis and microgliosis both contribute to basal ganglia pathology, the contribution of gliosis and potential factors driving glial activity in the human HD cerebral cortex is less understood. Our study aims to identify nuanced indicators of gliosis in HD which is challenging to identify in the severely degenerated basal ganglia, by investigating the middle temporal gyrus (MTG), a cortical region previously documented to demonstrate milder neuronal loss. Immunohistochemistry was conducted on MTG paraffin-embedded tissue microarrays (TMAs) comprising 29 HD and 35 neurologically normal cases to compare the immunoreactivity patterns of key astrocytic proteins (glial fibrillary acidic protein, GFAP; inwardly rectifying potassium channel 4.1, Kir4.1; glutamate transporter-1, GLT-1; aquaporin-4, AQP4), key microglial proteins (ionised calcium-binding adapter molecule-1, IBA-1; human leukocyte antigen (HLA)-DR; transmembrane protein 119, TMEM119; purinergic receptor P2RY12, P2RY12), and indicators of proliferation (Ki-67; proliferative cell nuclear antigen, PCNA). Our findings demonstrate an upregulation of GFAP+ protein expression attributed to the presence of more GFAP+ expressing cells in HD, which correlated with greater cortical mutant huntingtin (mHTT) deposition. In contrast, Kir4.1, GLT-1, and AQP4 immunoreactivity levels were unchanged in HD. We also demonstrate an increased number of IBA-1+ and TMEM119+ microglia with somal enlargement. IBA-1+, TMEM119+, and P2RY12+ reactive microglia immunophenotypes were also identified in HD, evidenced by the presence of rod-shaped, hypertrophic, and dystrophic microglia. In HD cases, IBA-1+ cells contained either Ki-67 or PCNA, whereas GFAP+ astrocytes were devoid of proliferative nuclei. These findings suggest cortical microgliosis may be driven by proliferation in HD, supporting the hypothesis of microglial proliferation as a feature of HD pathophysiology. In contrast, astrocytes in HD demonstrate an altered GFAP expression profile that is associated with the degree of mHTT deposition.

Background: Src homology 2 domain-containing phosphatase 2 (SHP2) is hyper-activated in some solid tumors. Previous findings suggest that the expression of SHP2 in colorectal cancer (CRC) may be associated with prognosis. However, validation with large sample data is lacking. Materials and Methods: Tissue microarrays containing 860 CRCs and 197 mucosal tissues adjacent to the tumors were constructed. Immunohistochemistry was used to evaluate the expression of SHP2. Differences between SHP2 expression and clinicopathological parameters were evaluated. Kaplan–Meier survival curves and log-rank tests were used to analyze the relationships between SHP2 expression and the overall survival of patients. A Cox proportional hazard regression model was used for univariate and multivariate analyses of prognostic factors. Results: SHP2 expression in CRCs tissues was significantly higher than those in adjacent mucosal tissues (P < 0.001). SHP2 expression was related to tumor differentiation, depth of invasion, distant metastasis, vascular tumor thrombus, lymph node metastasis, and TNM classification (P < 0.05). The prognosis of the high-expression group of SHP2 was significantly better than that of the low-expression group (P = 0.008). Univariate analysis showed that the expression of SHP2 was a prognostic factor for CRC (P = 0.008). Multivariate analysis demonstrated that SHP2 remained an independent prognostic factor for CRC (P = 0.033). Conclusion: The expression of SHP2 was significantly higher in CRC tissues than in adjacent normal tissues. High expression of SHP2 was associated with a promising outcome, suggesting that SHP2 may be a favorable prognostic indicator of CRC.

Background: c-MYC and BCL2 positivity are important prognostic factors for diffuse large B-cell lymphoma. However, manual quantification is subject to significant intra- and inter-observer variability. We developed an automated method for quantification in whole-slide images of tissue sections where manual quantification requires evaluating large areas of tissue with possibly heterogeneous staining. We train this method using annotations of tumor positivity in smaller tissue microarray cores where expression and staining are more homogeneous and then translate this model to whole-slide images. Methods: Our method applies a technique called attention-based multiple instance learning to regress the proportion of c-MYC-positive and BCL2-positive tumor cells from pathologist-scored tissue microarray cores. This technique does not require annotation of individual cell nuclei and is trained instead on core-level annotations of percent tumor positivity. We translate this model to scoring of whole-slide images by tessellating the slide into smaller core-sized tissue regions and calculating an aggregate score. Our method was trained on a public tissue microarray dataset from Stanford and applied to whole-slide images from a geographically diverse multi-center cohort produced by the Lymphoma Epidemiology of Outcomes study. Results: In tissue microarrays, the automated method had Pearson correlations of 0.843 and 0.919 with pathologist scores for c-MYC and BCL2, respectively. When utilizing standard clinical thresholds, the sensitivity/specificity of our method was 0.743 / 0.963 for c-MYC and 0.938 / 0.951 for BCL2. For double-expressors, sensitivity and specificity were 0.720 and 0.974. When translated to the external WSI dataset scored by two pathologists, Pearson correlation was 0.753 & 0.883 for c-MYC and 0.749 & 0.765 for BCL2, and sensitivity/specificity was 0.857/0.991 & 0.706/0.930 for c-MYC, 0.856/0.719 & 0.855/0.690 for BCL2, and 0.890/1.00 & 0.598/0.952 for double-expressors. Survival analysis demonstrates that for progression-free survival, model-predicted TMA scores significantly stratify double-expressors and non double-expressors (p = 0.0345), whereas pathologist scores do not (p = 0.128). Conclusions: We conclude that proportion of positive stains can be regressed using attention-based multiple instance learning, that these models generalize well to whole slide images, and that our models can provide non-inferior stratification of progression-free survival outcomes. [ABSTRACT FROM AUTHOR]

The cell cycle plays a key and complex role in the development of human cancers. p21 is a potent cyclin-dependent kinase inhibitor (CDKI) involved in the promotion of cell cycle arrest and the regulation of cellular senescence. Altered p21 expression in rectal cancer cells may affect tumor cells' behavior and resistance to neoadjuvant and adjuvant therapy. Our study aimed to ascertain the relationship between the differential expression of p21 in rectal cancer and patient survival outcomes. Using tissue microarrays, 266 rectal cancer specimens were immunohistochemically stained for p21. The expression patterns were scored separately in cancer cells retrieved from the center and the periphery of the tumor; compared with clinicopathological data, tumor regression grade (TRG), disease-free, and overall survival. Negative p21 expression in tumor periphery cells was significantly associated with longer overall survival upon the univariate (p = 0.001) and multivariable analysis (p = 0.003, HR = 2.068). Negative p21 expression in tumor periphery cells was also associated with longer disease-free survival in the multivariable analysis (p = 0.040, HR = 1.769). Longer overall survival times also correlated with lower tumor grades (p= 0.011), the absence of vascular and perineural invasion (p = 0.001; p < 0.005), the absence of metastases (p < 0.005), and adjuvant treatment (p = 0.009). p21 expression is a potential predictive and prognostic biomarker for clinical outcomes in rectal cancer patients. Negative p21 expression in tumor periphery cells demonstrated significant association with longer overall survival and disease-free survival. Larger prospective studies are warranted to investigate the ability of p21 to identify rectal cancer patients who will benefit from neoadjuvant and adjuvant therapy. [ABSTRACT FROM AUTHOR]

Most inactivating p53 mutations result in a nuclear p53 accumulation – detectable by immunohistochemistry (IHC). p53 alterations leading to a complete lack of p53 protein and absence of immunostaining do also occur – not easily detectable by IHC. p16 is upregulated in p53 inactivated cells. We hypothesized that a positive p16 IHC may help to distinguish p53 inactivation in IHC negative cases. We investigated p53 and p16 immunostaining on 2710 urothelial bladder carcinomas in a tissue microarray format to understand their impact in relation to clinicopathological parameters of disease progression and patient outcome. p16 immunostaining was absent in normal urothelium but occurred in 63.5% (30.4% strong) of cancers. p16 strongly positive cases increased from pTaG2 low-grade (9.6%) to pTaG3 high-grade tumors (46.5%, p <.0001) but decreased from pTaG3 to pT4 (33.3%; p =.0030). Among pT2-4 carcinomas, p16 positivity was linked to high-grade (p =.0005) but unrelated to overall survival. p53 staining was negative in 8.4%, very weak in 15.4%, weak in 55.3%, strong in 4.7%, and very strong in 16.2% cancers. p53 negative (potentially p53 null phenotype), strong, and very strong p53 positivity increased from pTaG2 low-grade to pTaG3 high-grade tumors (p <.0001) and from pTaG3 to pT2-4 cancers (p =.0007). p53 staining was largely unrelated to histopathological parameters or patient prognosis among pT2-4 carcinomas, except of p53 strong/very strong immunostaining. p16 expression predominated in tumors with very strong, strong, and negative p53 staining and the combination of p53 negative/p16 strongly positive cancers was linked to features of tumor aggressiveness. Aberrant p53 and p16 immunostaining increases during grade and stage progression although p53 negative and p16 positive immunostaining lack prognostic significance in pT2–4 carcinomas. Potential diagnostic features are that high level p16 expression is limited to neoplastic urothelium and p53 null phenotype to aggressive cancers (grade 3 and invasive). [ABSTRACT FROM AUTHOR]

Abstract Background Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells. Results We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells’ cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers. Conclusion The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level.

Background: Protein biomarkers of cancer progression and response to therapy are increasingly important for improving personalized medicine. Advanced quantitative pathology platforms enable measurement of protein expression in tissues at the single-cell level. However, this rich quantitative cell-by-cell biomarker information is most often not exploited. Instead, it is reduced to a single mean across the cells of interest or converted into a simple proportion of binary biomarker-positive or -negative cells. Results: We investigated the utility of retaining all quantitative information at the single-cell level by considering the values of the quantile function (inverse of the cumulative distribution function) estimated from a sample of cell signal intensity levels in a tumor tissue. An algorithm was developed for selecting optimal cutoffs for dichotomizing cell signal intensity distribution quantiles as predictors of continuous, categorical or survival outcomes. The proposed algorithm was used to select optimal quantile biomarkers of breast cancer progression based on cancer cells' cell signal intensity levels of nuclear protein Ki-67, Proliferating cell nuclear antigen, Programmed cell death 1 ligand 2, and Progesterone receptor. The performance of the resulting optimal quantile biomarkers was validated and compared to the standard cancer compartment mean signal intensity markers using an independent external validation cohort. For Ki-67, the optimal quantile biomarker was also compared to established biomarkers based on percentages of Ki67-positive cells. For proteins significantly associated with PFS in the external validation cohort, the optimal quantile biomarkers yielded either larger or similar effect size (hazard ratio for progression-free survival) as compared to cancer compartment mean signal intensity biomarkers. Conclusion: The optimal quantile protein biomarkers yield generally improved prognostic value as compared to the standard protein expression markers. The proposed methodology has a broad application to single-cell data from genomics, transcriptomics, proteomics, or metabolomics studies at the single cell level. [ABSTRACT FROM AUTHOR]

Simple Summary: We have previously shown that the glucocorticoid receptor (GCR) protein was reduced in invasive breast carcinoma compared to normal breast tissue. Here, we evaluated the level of serum/glucocorticoid-regulated kinase 1 (SGK1) and B-cell lymphoma 2 (Bcl-2) levels in the corresponding primary breast cancer tissue. SGK1 was higher and Bcl-2 was lower in breast cancer tissue compared to normal breast tissue. Similar to previous reports, we found that the expression of the Bcl-2 protein was associated with longer survival. We observed a correlation between the expression of the GCR and the Bcl-2 protein. The expression of the Bcl-2 protein was higher among cases who self-reported their race and ethnicity as non-Hispanic Black people. It is crucial to understand molecular alterations in breast cancer and how they relate to clinicopathologic factors. We have previously shown that the glucocorticoid receptor (GCR) protein expression was reduced in invasive breast carcinoma compared to normal breast tissue. Glucocorticoids, signaling through the GCR, regulate several cellular processes via downstream targets such as serum/glucocorticoid-regulated kinase 1 (SGK1) and B-cell lymphoma 2 (Bcl-2). We measured the expression of SGK1 and Bcl-2, in respective breast cancer tissue arrays, from a multiracial cohort of breast cancer patients. Higher cytoplasmic SGK1 staining was stronger in breast cancer tissue compared to normal tissue, especially in hormone receptor-negative cases. Conversely, the expression of cytoplasmic Bcl-2 was reduced in breast cancer compared to normal tissue, especially in hormone receptor-negative cases. Bcl-2 staining was associated with the self-reported racial/ethnic category, an earlier clinical stage, a lower histological grade, and a higher survival rate. Bcl-2 expression was associated with longer survival in models adjusted for age and race (HR = 0.32, 95% CI: 0.15, 0.65), and Bcl-2 expression remained strongly positively associated with protection from breast cancer death, with additional adjustments for ER/PR status (HR = 0.41, 95% CI: 0.2, 0.85). SGK1 and Bcl-2 may play biological roles in breast cancer development and/or progression. [ABSTRACT FROM AUTHOR]

The cell cycle plays a key and complex role in the development of human cancers. p21 is a potent cyclin-dependent kinase inhibitor (CDKI) involved in the promotion of cell cycle arrest and the regulation of cellular senescence. Altered p21 expression in rectal cancer cells may affect tumor cells’ behavior and resistance to neoadjuvant and adjuvant therapy. Our study aimed to ascertain the relationship between the differential expression of p21 in rectal cancer and patient survival outcomes. Using tissue microarrays, 266 rectal cancer specimens were immunohistochemically stained for p21. The expression patterns were scored separately in cancer cells retrieved from the center and the periphery of the tumor; compared with clinicopathological data, tumor regression grade (TRG), disease-free, and overall survival. Negative p21 expression in tumor periphery cells was significantly associated with longer overall survival upon the univariate (p = 0.001) and multivariable analysis (p = 0.003, HR = 2.068). Negative p21 expression in tumor periphery cells was also associated with longer disease-free survival in the multivariable analysis (p = 0.040, HR = 1.769). Longer overall survival times also correlated with lower tumor grades (p= 0.011), the absence of vascular and perineural invasion (p = 0.001; p < 0.005), the absence of metastases (p < 0.005), and adjuvant treatment (p = 0.009). p21 expression is a potential predictive and prognostic biomarker for clinical outcomes in rectal cancer patients. Negative p21 expression in tumor periphery cells demonstrated significant association with longer overall survival and disease-free survival. Larger prospective studies are warranted to investigate the ability of p21 to identify rectal cancer patients who will benefit from neoadjuvant and adjuvant therapy.

Background/Aim: Meningiomas represent the main intracranial primary central nervous system (CNS) tumour in adults worldwide. Oncogenes' over-activation combined with suppressor genes' silencing affect negatively the biological behavior of these neoplasms. This study aimed to explore the impact of p53 suppressor gene expression in meningiomas' clinic-pathological features based on a combination of sophisticated techniques. Materials and Methods: Fifty (n=50) meningiomas were included in the study, comprising a broad spectrum of histopathological subtypes. An immunohistochemistry assay was applied on tissue microarray cores followed by digital image analysis. Results: p53 protein over-expression (high staining intensity levels) was observed in 27/50 (54%) cases, whereas the rest (23/50-/46%) demonstrated moderate to low levels of the protein. p53 over-expression was statistically significantly correlated to the mitotic index of the examined cases (p-value=0.001). Interestingly, the atypical/anaplastic group of histotypes demonstrated the strongest p53 expression rates compared to the others (p-value=0.001). Conclusion: p53 overexpression is observed in a broad spectrum of meningiomas. High expression levels lead to an aggressive biological behavior of the malignancy (combined with increased mitotic rates), especially in atypical and anaplastic sub-types that also have a high recurrence rate. [ABSTRACT FROM AUTHOR]

Cancer/Testis (CT) genes are induced in germ cells, repressed in somatic cells, and derepressed in somatic tumors, where these genes can contribute to cancer progression. CT gene identification requires data obtained using standardized protocols and technologies. This is a challenge because data for germ cells, gonads, normal somatic tissues, and a wide range of cancer samples stem from multiple sources and were generated over substantial periods of time. We carried out a GeneChip‐based RNA profiling analysis using our own data for testis and enriched germ cells, data for somatic cancers from the Expression Project for Oncology, and data for normal somatic tissues from the Gene Omnibus Repository. We identified 478 candidate loci that include known CT genes, numerous genes associated with oncogenic processes, and novel candidates that are not referenced in the Cancer/Testis Database (www.cta.lncc.br). We complemented RNA expression data at the protein level for SPESP1, GALNTL5, PDCL2, and C11orf42 using cancer tissue microarrays covering malignant tumors of breast, uterus, thyroid, and kidney, as well as published RNA profiling and immunohistochemical data provided by the Human Protein Atlas (www.proteinatlas.org). We report that combined RNA/tissue profiling identifies novel CT genes that may be of clinical interest as therapeutical targets or biomarkers. Our findings also highlight the challenges of detecting truly germ cell‐specific mRNAs and the proteins they encode in highly heterogenous testicular, somatic, and tumor tissues.

The incidence of breast cancer is tending younger globally, and tumor development, clinical treatment, and prognosis are largely influenced by histopathological diagnosis. For diagnosed patients, the distinction between the cancer nests and normal tissue is the basis of breast cancer treatment. Microscopic hyperspectral imaging technology has shown its potential in auxiliary pathological examinations due to the superior imaging modality and data characteristics. This paper presents a method for cancer nest segmentation from hyperspectral images of breast cancer tissue microarray samples. The scheme combines the strengths of the U-Net neural network and unsupervised principal component analysis, which reduces the amount of calculation and improves the recognition accuracy. The experimental accuracy of cancer nest segmentation reaches 87.14%. Furthermore, a set of quantitative pathological characteristic parameters reflects the degree of breast cancer lesions from multiple angles, providing a relatively comprehensive reference for the pathologist's diagnosis. In-depth exploration of the combined development of deep learning and microscopic hyperspectral imaging technology is worthy to promote efficient diagnosis of breast tumors and concern for human health.

Huntington's disease (HD) is caused by a CAG repeat expansion mutation in the gene encoding the huntingtin (Htt) protein, with mutant Htt protein subsequently forming aggregates within the brain. Mutant Htt is a current target for novel therapeutic strategies for HD, however, the lack of translation from preclinical research to disease-modifying treatments highlights the need to improve our understanding of the role of Htt protein in the human brain. This study aims to undertake an immunohistochemical screen of 12 candidate antibodies against various sequences along the Htt protein to characterize Htt distribution and expression in post-mortem human brain tissue microarrays (TMAs).Immunohistochemistry was performed on middle temporal gyrus TMAs comprising of up to 28 HD and 27 age-matched control cases, using 12 antibodies specific to various sequences along the Htt protein. From this study, six antibodies directed to the Htt N-terminus successfully immunolabeled human brain tissue. Htt aggregates and Htt protein expression levels for the six successful antibodies were subsequently quantified with a customized automated image analysis pipeline on the TMAs. A 2.5–12 fold increase in the number of Htt aggregates were detected in HD cases using antibodies MAB5374, MW1, and EPR5526, despite no change in overall Htt protein expression compared to control cases, suggesting a redistribution of Htt into aggregates in HD. MAB5374, MW1, and EPR5526 Htt aggregate numbers were positively correlated with CAG repeat length, and negatively correlated with the age of symptom onset in HD. However, the number of Htt aggregates did not correlate with the degree of striatal degeneration or the degree of cortical neuron loss. Together, these results suggest that longer CAG repeat lengths correlate with Htt aggregation in the HD human brain, and greater Htt cortical aggregate deposition is associated with an earlier age of symptom onset in HD. This study also reinforces that antibodies MAB5492, MW8, and 2B7 which have been utilized to characterize Htt in animal models of HD do not specifically immunolabel Htt aggregates in HD human brain tissue exclusively, thereby highlighting the need for validated means of Htt detection to support drug development for HD.

Simple Summary: The identification of effective novel biomarkers is emergently needed in colon cancer patients. In the present study, firstly we predicted that CHGA could be a biomarker for colon cancer based on the protein–protein interaction network of all the reported biomarkers that were collected from our colorectal cancer biomarker database (CBD). Then we verified our results using a diagnostic test in gene expression data and an immunohistochemistry test. The results of this study suggest that a loss of CHGA expression from the normal colon and adjacent mucosa to colon cancer may be used as a valuable biomarker for early diagnosis of colon cancer patients. Background. The incidence of colorectal cancers has been constantly increasing. Although the mortality has slightly decreased, it is far from satisfaction. Precise early diagnosis for colorectal cancer has been a great challenge in order to improve patient survival. Patients and Methods. We started with searching for protein biomarkers based on our colorectal cancer biomarker database (CBD), finding differential expressed genes (GEGs) and non-DEGs from RNA sequencing (RNA-seq) data, and further predicted new biomarkers of protein–protein interaction (PPI) networks by machine learning (ML) methods. The best-selected biomarker was further verified by a receiver operating characteristic (ROC) test from microarray and RNA-seq data, biological network, and functional analysis, and immunohistochemistry in the tissue arrays from 198 specimens. Results. There were twelve proteins (MYO5A, CHGA, MAPK13, VDAC1, CCNA2, YWHAZ, CDK5, GNB3, CAMK2G, MAPK10, SDC2, and ADCY5) which were predicted by ML as colon cancer candidate diagnosis biomarkers. These predicted biomarkers showed close relationships with reported biomarkers of the PPI network and shared some pathways. An ROC test showed the CHGA protein with the best diagnostic accuracy (AUC = 0.9 in microarray data and 0.995 in RNA-seq data) among these candidate protein biomarkers. Furthermore, immunohistochemistry examination on our colon cancer tissue microarray samples further confirmed our bioinformatical prediction, indicating that CHGA may be used as a potential biomarker for early diagnosis of colon cancer patients. Conclusions. CHGA could be a potential candidate biomarker for diagnosing earlier colon cancer in the patients. [ABSTRACT FROM AUTHOR]

Huntington's disease (HD) is a neurodegenerative disorder that severely affects the basal ganglia and regions of the cerebral cortex. While astrocytosis and microgliosis both contribute to basal ganglia pathology, the contribution of gliosis and potential factors driving glial activity in the human HD cerebral cortex is less understood. Our study aims to identify nuanced indicators of gliosis in HD which is challenging to identify in the severely degenerated basal ganglia, by investigating the middle temporal gyrus (MTG), a cortical region previously documented to demonstrate milder neuronal loss. Immunohistochemistry was conducted on MTG paraffin-embedded tissue microarrays (TMAs) comprising 29 HD and 35 neurologically normal cases to compare the immunoreactivity patterns of key astrocytic proteins (glial fibrillary acidic protein, GFAP; inwardly rectifying potassium channel 4.1, Kir4.1; glutamate transporter-1, GLT-1; aquaporin-4, AQP4), key microglial proteins (ionised calcium-binding adapter molecule-1, IBA-1; human leukocyte antigen (HLA)-DR; transmembrane protein 119, TMEM119; purinergic receptor P2RY12, P2RY12), and indicators of proliferation (Ki-67; proliferative cell nuclear antigen, PCNA). Our findings demonstrate an upregulation of GFAP+ protein expression attributed to the presence of more GFAP+ expressing cells in HD, which correlated with greater cortical mutant huntingtin (mHTT) deposition. In contrast, Kir4.1, GLT-1, and AQP4 immunoreactivity levels were unchanged in HD. We also demonstrate an increased number of IBA-1+ and TMEM119+ microglia with somal enlargement. IBA-1+, TMEM119+, and P2RY12+ reactive microglia immunophenotypes were also identified in HD, evidenced by the presence of rod-shaped, hypertrophic, and dystrophic microglia. In HD cases, IBA-1+ cells contained either Ki-67 or PCNA, whereas GFAP+ astrocytes were devoid of proliferative nuclei. These findings suggest cortical microgliosis may be driven by proliferation in HD, supporting the hypothesis of microglial proliferation as a feature of HD pathophysiology. In contrast, astrocytes in HD demonstrate an altered GFAP expression profile that is associated with the degree of mHTT deposition. • Cytoskeletal astrocytic protein expression is altered in Huntington's disease. • Astrocytic functional protein expression in the cerebral cortex is preserved. • Microglia proliferation is a feature of cortical Huntington's disease pathology. • Huntington's disease cortex presents with various reactive microglia morphologies. [ABSTRACT FROM AUTHOR]

The plasminogen activation system regulates the activity of the serine protease, plasmin. The role of plasminogen receptors in cancer progression is being increasingly appreciated as key players in modulation of the tumor microenvironment. The interaction of plasminogen with cells to promote plasminogen activation requires the presence of proteins exposing C-terminal lysines on the cell surface. Plg-RKT is a structurally unique plasminogen receptor because it is an integral membrane protein that is synthesized with and binds plasminogen via a C-terminal lysine exposed on the cell surface. Here, we have investigated the expression of Plg-RKT in human breast tumors and human breast cancer cell lines. Breast cancer progression tissue microarrays were probed with anti-Plg-RKT mAB and we found that Plg-RKT is widely expressed in human breast tumors, that its expression is increased in tumors that have spread to draining lymph nodes and distant organs, and that Plg-RKT expression is most pronounced in hormone receptor (HR)-positive tumors. Plg-RKT was detected by Western blotting in human breast cancer cell lines. By flow cytometry, Plg-RKT cell surface expression was highest on the most aggressive tumor cell line. Future studies are warranted to address the functions of Plg-RKT in breast cancer. [ABSTRACT FROM AUTHOR]

The stage I uterine malignant mixed mullerian tumor (MMMT) shows different potential for progression. We reason that MMMTs with high-grade carcinomatous component and positivity for HB-EGF are prone to recurrence/metastasis in the early stage. A retrospective clinical and histopathologic review with immunohistochemical staining for HB-EGF, EGFR, and integrin-α5 was performed for 62 surgically staged MMMT cases. Recurrence/metastasis (RM) is 6/18 (33%) in stage I disease. Of all the clinicopathologic variables and biomarkers analyzed for stage I MMMT, serous carcinomatous component (83% [5/6] versus 17% [1/12], P = .0015) and HB-EGF expression (100% [6/6] versus 50% [6/12], P=.0339) were significantly different between groups with RM and without RM. The presence of serous carcinoma in all stages was 83% (5/6) in stage I with RM, 8% (1/12) in stage I without RM, 20% (1/5) in stage II, 36.4% (8/22) in stage III and 64.7% (11/17) in stage IV; this was paralleled by HB-EGF expression of 100% (6/6), 50% (6/12), 40% (2/5), 50% (11/22) and 71% (12/17) with a correlation coefficient r=0.9131 (P=.027). HB-EGF and integrin-α5 were highly expressed in MMMTs bearing serous carcinoma component, compared to endometrioid and unclassifiable/miscellaneous subtypes (84.6%/47.6%/33.3%, P=.025 for HB-EGF; and 61.5%/42.9%/20.0%, P=.021 for integrin-α5). The EGFR positivity was comparable among the three subtypes (48.1%, 47.6% and 26.7%, P=.326). This study indicates that serous carcinomatous component championed by expression of HB-EGF predisposes to recurrence/metastasis in stage I MMMT. This process might involve integrin-α5 and does not seem to require overexpression of EGFR. Further study is required.

Joanne Watt, Daniel G Maguire, Cherith N Reid, John V Lamont, Stephen P Fitzgerald, Mark W Ruddock Randox Laboratories Ltd, Molecular Biology, Crumlin, County Antrim BT29 4QY, Northern Ireland, UKCorrespondence: Mark W RuddockRandox Laboratories Ltd, Molecular Biology, 55 Diamond Road, Crumlin, County Antrim BT29 4QY, Northern Ireland, United KingdomTel +44 28 9442 2413Fax +44 28 9445 2912Email Mark.Ruddock@randox.comBackground: Decreased expression of thrombomodulin (TM) in bladder cancer tissue has been shown to be associated with cell proliferation, increased malignancy and a poor prognosis. The aim of this study was to investigate the immunoexpression of TM in bladder tissue cores by immunohistochemistry (IHC) and the relationship between TM score and patient survival for the following pathologies: transitional cell papillary carcinoma (TCPC), transitional cell carcinoma (non-papillary) (TCC), squamous cell carcinoma (SCC), adenocarcinoma, and sarcoma. TM immunoexpression was also evaluated in normal adjacent bladder tissue cores.Methods: TM immunoexpression was assessed in n=185 formalin-fixed paraffin-embedded (FFPE) bladder tissue cores from n=98 patients by IHC. Tissue cores included TCPC (n=29), TCC (n=85), SCC (n=21), adenocarcinoma (n=12), sarcoma (n=4), and normal tissue cores (n=34).Results: TM immunoexpression scores are stronger in TCPC, TCC and SCC bladder cancer tissue cores with respect to adenocarcinoma and sarcoma (mean TM immunoexpression scores: 3.04, 2.57, 2.55, 1.55 and 1.19, respectively) (Kruskal–Wallis p< 0.001). TM immunoexpression scores significantly decreased in bladder cancer tissue cores across both stage (p< 0.001) and grade (p< 0.001) (Kruskal–Wallis). Survival data were available for n=45 bladder cancer patients (mean follow-up of 34 months). Applying a TM immunoexpression cut-off score of 3.0 demonstrated that patients with bladder cancer who had a TM immunoexpression score < 3.0 had lower survival rates (median survival 23.5 months). In contrast, patients with TM immunoexpression scores ≥ 3.0 had longer survival rates (median survival 40 months) (log-rank; p=0.045).Conclusion: TM immunoexpression in bladder cancer tissue may be a clinically relevant predictor of tumor progression and survival. Low expression of TM in bladder cancer biopsies or in recurrent bladder cancer may be indicative of a poor prognosis. TM immunoexpression could be used to guide clinical decision making.Keywords: transitional urothelial carcinoma, tissue microarrays, immunohistochemistry, bladder cancer

Gliomas are primary brain tumors that arise from neural stem cells, or glial precursors. Diagnosis of glioma is based on histological evaluation of pathological cell features and molecular markers. Gliomas are infiltrated by myeloid cells that accumulate preferentially in malignant tumors, and their abundance inversely correlates with survival, which is of interest for cancer immunotherapies. To avoid time-consuming and laborious manual examination of images, a deep learning approach for automatic multiclass classification of tumor grades was proposed. As an alternative way of investigating characteristics of brain tumor grades, we implemented a protocol for learning, discovering, and quantifying tumor microenvironment elements on our glioma dataset. Using only single-stained biopsies we derived characteristic differentiating tumor microenvironment phenotypic neighborhoods. The study was complicated by the small size of the available human leukocyte antigen stained on glioma tissue microarray dataset - 206 images of 5 classes - as well as imbalanced data distribution. This challenge was addressed by image augmentation for underrepresented classes. In practice, we considered two scenarios, a whole slide supervised learning classification, and an unsupervised cell-to-cell analysis looking for patterns of the microenvironment. In the supervised learning investigation, we evaluated 6 distinct model architectures. Experiments revealed that a DenseNet121 architecture surpasses the baseline's accuracy by a significant margin of 9% for the test set, achieving a score of 69%, increasing accuracy in discerning challenging WHO grade 2 and 3 cases. All experiments have been carried out in a cross-validation manner. The tumor microenvironment analysis suggested an important role for myeloid cells and their accumulation in the context of characterizing glioma grades. Those promising approaches can be used as an additional diagnostic tool to improve assessment during intraoperative examination or subtyping tissues for treatment selection, potentially easing the workflow of pathologists and oncologists., (© 2024. The Author(s).)

Cancer/Testis (CT) genes are induced in germ cells, repressed in somatic cells, and derepressed in somatic tumors, where these genes can contribute to cancer progression. CT gene identification requires data obtained using standardized protocols and technologies. This is a challenge because data for germ cells, gonads, normal somatic tissues, and a wide range of cancer samples stem from multiple sources and were generated over substantial periods of time. We carried out a GeneChip‐based RNA profiling analysis using our own data for testis and enriched germ cells, data for somatic cancers from the Expression Project for Oncology, and data for normal somatic tissues from the Gene Omnibus Repository. We identified 478 candidate loci that include known CT genes, numerous genes associated with oncogenic processes, and novel candidates that are not referenced in the Cancer/Testis Database (www.cta.lncc.br). We complemented RNA expression data at the protein level for SPESP1, GALNTL5, PDCL2, and C11orf42 using cancer tissue microarrays covering malignant tumors of breast, uterus, thyroid, and kidney, as well as published RNA profiling and immunohistochemical data provided by the Human Protein Atlas (www.proteinatlas.org). We report that combined RNA/tissue profiling identifies novel CT genes that may be of clinical interest as therapeutical targets or biomarkers. Our findings also highlight the challenges of detecting truly germ cell‐specific mRNAs and the proteins they encode in highly heterogenous testicular, somatic, and tumor tissues. [ABSTRACT FROM AUTHOR]

Purpose: Glioblastoma, the most common malignant brain tumor, was associated with a median survival of <1 year in the pre-temozolomide (TMZ) era. Despite advances in molecular and genetic profiling studies identifying several predictive biomarkers, none has been translated into routine clinical use. Our aim was to investigate the prognostic significance of a panel of diverse cellular molecular markers of tumor formation and growth in an annotated glioblastoma tissue microarray (TMA). Methods and Materials: A TMA composed of archived glioblastoma tumors from patients treated with surgery, radiation, and non-TMZ chemother-apy, was provided by RTOG. RAD51, BRCA-1, phosphatase and tensin homolog tumor suppressor gene (PTEN), and miRNA-210 expression levels were assessed using quantitative in situ hybridization and automated quantitative protein analysis. The objectives of this analysis were to determine the association of each biomarker with overall survival (OS), using the Cox proportional hazard model. Event-time distributions were estimated using the Kaplan-Meier method and compared by the log-rank test. Results: A cohort of 66 patients was included in this study. Among the 4 biomarkers assessed, only BRCA1 expression had a statistically significant correlation with survival. From univariate analysis, patients with low BRCA1 protein expression showed a favorable outcome for OS (p = 0.04; hazard ratio = 0.56) in comparison with high expressors, with a median survival time of 18.9 versus 4.8 months. Conclusions: BRCA1 protein expression was an important survival predictor in our cohort of glioblastoma patients. This result may imply that low BRCA1 in the tumor and the consequent low level of DNA repair cause vulnerability of the cancer cells to treatment. [ABSTRACT FROM AUTHOR]

"Multi-Omics" technologies have contributed greatly to the understanding of various diseases by enabling researchers to accurately and rapidly investigate the molecular circuitry that connects cellular systems. The tissue-engineered, three-dimensional (3D), in vitro disease model "organoid" integrates the "omics" results in a model system, elucidating the complex links between genotype and phenotype. These 3D structures have been used to model cancer, infectious disease, toxicity, and neurological disorders. Here, we describe the advantage of using the tissue microarray (TMA) technology to analyze human-induced pluripotent stem cell–derived cerebral organoids. Compared with the conventional processing of individual samples, sectioning and staining of TMA slides are faster and can be automated, decreasing labor and reagent costs. The TMA technology faithfully captures cell morphology variations and detects specific biomarkers. The use of this technology can scale up organoid research results in at least two ways: (1) in the number of specimens that can be analyzed simultaneously and (2) in the number of consecutive sections that can be produced for analysis with different probes and antibodies. [ABSTRACT FROM AUTHOR]

The plasminogen activation system regulates the activity of the serine protease, plasmin. The role of plasminogen receptors in cancer progression is being increasingly appreciated as key players in modulation of the tumor microenvironment. The interaction of plasminogen with cells to promote plasminogen activation requires the presence of proteins exposing C-terminal lysines on the cell surface. Plg-RKT is a structurally unique plasminogen receptor because it is an integral membrane protein that is synthesized with and binds plasminogen via a C-terminal lysine exposed on the cell surface. Here, we have investigated the expression of Plg-RKT in human breast tumors and human breast cancer cell lines. Breast cancer progression tissue microarrays were probed with anti-Plg-RKT mAB and we found that Plg-RKT is widely expressed in human breast tumors, that its expression is increased in tumors that have spread to draining lymph nodes and distant organs, and that Plg-RKT expression is most pronounced in hormone receptor (HR)-positive tumors. Plg-RKT was detected by Western blotting in human breast cancer cell lines. By flow cytometry, Plg-RKT cell surface expression was highest on the most aggressive tumor cell line. Future studies are warranted to address the functions of Plg-RKT in breast cancer.

Purpose: Enhancer of zeste homolog 2 (EZH2), the catalytic part of the Polycomb repressive complex 2 (PRC2), has a prognostic role in renal cell carcinoma (RCC) and was recently shown to modulate the immune response by reducing tumor cell immunogenicity. Methods: To investigate whether the prognostic role of EZH2 might be driven by a modified immune environment, more than 1800 RCCs were analyzed in a tissue microarray for EZH2 expression and CD8 positive lymphocytes were quantitated by automated digital imaging. Results: EZH2 positivity was found in 75.2% of 1603 interpretable tumors. In clear cell RCC, high EZH2 expression was significantly linked to high ISUP, Furmann, and Thoenes grade (p < 0.0001 each), advanced stage (p < 0.0001), nodal (p = 0.0190) and distant metastasis (p < 0.0001) as well as shortened overall (p < 0.0027) and recurrence free survival (p < 0.0001). The density of CD8+ cells varied from 0 to 5048 cells/mm2 (Median 120 cells/mm2). A high CD8+ count was significantly associated with high ISUP, Fuhrmann, and Thoenes grade (p < 0.0001 each), advanced tumor stage (p = 0.0041), distant metastasis (p = 0.0026) as well as reduced overall survival (p = 0.0373) and recurrence free survival (p = 0.0450). The density of CD8+ cells continuously increased with raising EZH2 levels (p < 0.0001). Conclusion: Our data support a striking prognostic role of both EZH2 expression and the density of CD8+ cells in RCC. The tight relationship of EZH2 expression and CD8+ cell counts in RCC is consistent with models suggesting that EZH2 overexpression can be caused by high lymphocyte content in certain tumor types. Such a mechanism could explain the unique finding of high lymphocyte counts driving poor prognosis in RCC patients. [ABSTRACT FROM AUTHOR]

HHLA2, a newly identified B7 family member, regulates T cell functions. However, the expression and prognostic value of HHLA2 in solid tumors is ill defined. This study aimed to reveal the expression landscape of HHLA2 in various solid tumors, and to evaluate its prognostic value in kidney clear cell carcinoma (KIRC). Using The Cancer Genome Atlas (TCGA) database, we investigated the expression pattern of HHLA2 across 22 types of cancer. HHLA2 and CD8 protein expression was determined via immunohistochemistry (IHC). KIRC-specific findings were further analyzed with R software and the prognostic value was validated on tissue microarrays. HHLA2 was widely expressed in cancers at both the mRNA and protein levels. Among all tested tumors, KIRC showed the highest transcript level of HHLA2, and HHLA2 levels were significantly higher in tumor tissues than in matched normal samples, as evidenced by both TCGA and IHC data. HHLA2 was also positively correlated with survival rates in KIRC based on TCGA and clinical data. Receiver operating characteristic curves data showed the prognostic value of HHLA2 for patients with KIRC in TCGA. Moreover, HHLA2 was positively correlated with immune-related genes, while HHLA2 and CD8 expression exhibited a consistent trend in KIRC tumor samples. In conclusion, HHLA2 is highly expressed in KIRC and predicts a favorable survival outcome, highlighting that it may work as a potential target for KIRC therapy.

Traditionally regarded to coordinate movement, the cerebellum also exerts non-motor functions including the regulation of cognitive and behavioral processing, suggesting a potential role in neurodegenerative conditions affecting cognition, such as Alzheimer's disease (AD). This study aims to investigate neuropathology and AD-related molecular changes within the neocerebellum using post-mortem human brain tissue microarrays (TMAs).Immunohistochemistry was conducted on neocerebellar paraffin-embedded TMAs from 24 AD and 24 matched control cases, and free-floating neocerebellar sections from 6 AD and 6 controls. Immunoreactivity was compared between control and AD groups for neuropathological hallmarks (amyloid-β, tau, ubiquitin), Purkinje cells (calbindin), microglia (IBA1, HLA-DR), astrocytes (GFAP) basement-membrane associated molecules (fibronectin, collagen IV), endothelial cells (CD31/PECAM-1) and mural cells (PDGFRβ, αSMA).Amyloid-β expression (total immunolabel intensity) and load (area of immunolabel) was increased by >4-fold within the AD cerebellum. Purkinje cell counts, ubiquitin and tau immunoreactivity were unchanged in AD. IBA1 expression and load was increased by 91% and 69%, respectively, in AD, with no change in IBA1-positive cell number. IBA1-positive cell process length and branching was reduced by 22% and 41%, respectively, in AD. HLA-DR and GFAP immunoreactivity was unchanged in AD. HLA-DR-positive cell process length and branching was reduced by 33% and 49%, respectively, in AD. Fibronectin expression was increased by 27% in AD. Collagen IV, PDGFRβ and αSMA immunoreactivity was unchanged in AD. The number of CD31-positive vessels was increased by 98% in AD, suggesting the increase in CD31 expression and load in AD is due to greater vessel number. The PDGFRβ/CD31 load ratio was reduced by 59% in AD.These findings provide evidence of molecular changes affecting microglia and the neurovasculature within the AD neocerebellum. These changes, occurring without overt neuropathology, support the hypothesis of microglial and neurovascular dysfunction as drivers of AD, which has implications on the neocerebellar contribution to AD symptomatology and pathophysiology.

Leiomyosarcoma (LMS) is a soft tissue tumor with a significant degree of morphologic and molecular heterogeneity. We used integrative molecular profiling to discover and characterize molecular subtypes of LMS. Gene expression profiling was performed on 51 LMS samples. Unsupervised clustering showed three reproducible LMS clusters. Array comparative genomic hybridization (aCGH) was performed on 20 LMS samples and showed that the molecular subtypes defined by gene expression showed distinct genomic changes. Tumors from the 'muscle-enriched' cluster showed significantly increased copy number changes (P=0.04). A majority of the muscle-enriched cases showed loss at 16q24, which contains Fanconi anemia, complementation group A, known to have an important role in DNA repair, and loss at 1p36, which contains PRDM16, of which loss promotes muscle differentiation. Immunohistochemistry (IHC) was performed on LMS tissue microarrays (n=377) for five markers with high levels of messenger RNA in the muscle-enriched cluster (ACTG2, CASQ2, SLMAP, CFL2 and MYLK) and showed significantly correlated expression of the five proteins (all pairwise P

Background and Objective: The aim of this study was to investigate the value of programmed death ligand 1 (PD-L1) expression as a predictive biomarker for Miller/Payne grading before neoadjuvant chemotherapy (NACT) in breast cancer. Patients and Methods: The expression of PD-L1 in pretreatment biopsies of breast cancer was assessed by immunohistochemistry in tissue microarrays. The results were analyzed using SPSS 22.0 statistical software. Results: Of 53 female patients, 10 (18.9%) patients had a grade 5 (G5) response, and 12 (22.6%) patients showed PD-L1 expression, including 7 (13.2%) patients with staining in tumor cells (TCs) and 8 (15.1%) patients with staining in peritumoral lymphocytes (PTLCs). Logistic regression analysis revealed that G5 response to NACT was significantly associated with TCs or PTLCs PD-L1 positivity, whether with univariate analysis (TCs PD-L1: p = 0.00, OR 20.50, 95% CI 3.11–134.94; PTLCs PD-L1: p = 0.02, OR 6.50, 95% CI 1.27–33.20) or with multivariate analysis (TCs PD-L1: p = 0.00, OR 42.23, 95% CI 3.36–530.90; PTLCs PD-L1: p = 0.02, OR 9.07, 95% CI 1.37–60.02). The same trend was found in the luminal subgroup analysis (TCs PD-L1: p = 0.02, OR 23.43, 95% CI 1.66–331.58; PTLCs PD-L1: p = 0.01, OR 47.89, 95% CI 2.47–927.41). Conclusion: G5 response to NACT in breast cancer was significantly associated with TCs or PTLCs PD-L1-positive expression in pretreatment biopsies; it can be expected that PD-L1 will become a new independent biomarker of response to NACT in breast cancer. [ABSTRACT FROM AUTHOR]

Clinically relevant epidermal tumours in dogs include cutaneous papillomas (CPs) and cutaneous squamous cell carcinomas (CSCCs). The development of CPs and CSCCs involves dysregulation in expression of E-cadherin/β-catenin; however, knowledge about the contribution of these molecules to epidermal tumourigenesis in dogs is limited. This study examined the immunohistochemical expression pattern of E-cadherin/β-catenin in samples of normal canine epidermis, CPs, preneoplastic epidermis and CSCCs, using tissue microarrays, in order to elucidate whether the dysregulated expression of these molecules may contribute to the pathogenesis of clinically relevant epidermal tumours in dogs. We also investigated the correlation between the immunohistochemical expression pattern of E-cadherin/β-catenin in these tissue microarrays to further evaluate whether the disruption of the adherens junction interactions plays a relevant role in canine epidermal tumourigenesis. In samples of CP and preneoplastic epidermis, the membrane immunoreactivity of E-cadherin/β-catenin was conserved, while in CSCC, the immunoreactivity of these molecules was significantly reduced, independently of the tumour location. There was significant correlation between the membrane expression of E-cadherin/β-catenin in CSCC. β-catenin also showed cytoplasmic and nuclear expression in samples of CP, preneoplastic epidermis and CSCC. These results support the hypothesis that dysregulated expression of E-cadherin/β-catenin may play a critical role in the pathogenesis of relevant canine epidermal tumours, not only due to the disruption of the intercellular adherens junctions, but also due to the dysregulated activity of the signalling pathways in which these molecules are involved. [ABSTRACT FROM AUTHOR]

• In human OSCC, VISTA is expressed on MDSCs in PBMCs and is more stable than PD-L1. • VISTA in human and transgenic mouse OSCC tissues was correlated with MDSCs. • VISTA blockade significantly alleviated the tumor growth of 4MOSC1 and 4MOSC2 OSCC-bearing mice. • VISTA blockade reduced MDSCs and boosted CD8+ T cell mediated antitumor effect. • T RM are the main subsets that increases after VISTA blockade. V-domain Ig suppressor of T-cell activation (VISTA) is a novel immune checkpoint regulator that can inhibit T cell-mediated antitumor immunity. Although the use of anti-VISTA monoclonal antibody has demonstrated encouraging outcomes in the therapy of various malignancies, its specific impact and underlying mechanisms in oral squamous cell carcinoma (OSCC) remain to be explored. In this work, we analyzed human OSCC tissue microarrays, human peripheral blood mononuclear cells, and immunocompetent transgenic mouse models to investigate the relationship between high VISTA expression and markers of myeloid-derived immunosuppressive cells (MDSCs; CD11b, CD33, Arginase-1), tumor-associated macrophages (CD68, CD163, CD206), and T cell function (CD8, PD-L1, Granzyme B). In OSCC, we discovered that VISTA was highly expressed and stably expressed in MDSCs. Furthermore, we established a mouse OSCC orthotopic xenograft tumor model to investigate the impact of VISTA blockade on the tumor microenvironment. We found that VISTA blockade reduces the immunosuppressive microenvironment and delays tumor growth. This is achieved by suppressing the quantity and function of MDSCs while boosting the function of tumor-infiltrating T cells. Our research indicated that VISTA expressed by MDSCs has a crucial function in the progression of OSCC and that VISTA blockade therapy is a promising immune checkpoint blockade therapy. [ABSTRACT FROM AUTHOR]

Colorectal cancer (CRC) is the leading cause of cancer death, but little is known about its etiopathology. Aldo-keto reductase 1B10 (AKR1B10) protein is primarily expressed in intestinal epithelial cells, but lost in colorectal cancer tissues. This study revealed that AKR1B10 may not be a prognostic but an etiological factor in colorectal tumorigenesis. Using a tissue microarray, we investigated the expression of AKR1B10 in tumor tissues of 592 colorectal cancer patients with a mean follow-up of 25 years. Results exhibited that AKR1B10 protein was undetectable in 374 (63.13%), weakly positive in 146 (24.66%), and positive 72 (12.16%) of 592 tumor tissues. Kaplan-Meier analysis showed that AKR1B10 expression was not correlated with overall survival or disease-free survival. Similar results were obtained in various survival analyses stratified by clinicopathological parameters. AKR1B10 was not correlated with tumor T-pathology, N-pathology, TNM stages, cell differentiation and lymph node/regional/distant metastasis either. However, AKR1B10 silencing in culture cells enhanced carbonyl induced protein and DNA damage; and in ulcerative colitis tissues, AKR1B10 deficiency was associated acrolein-protein lesions. Together this study suggests that AKR1B10 downregulation may not be a prognostic but a carcinogenic factor of colorectal cancer., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Background: Src homology 2 domain-containing phosphatase 2 (SHP2) is hyper-activated in some solid tumors. Previous findings suggest that the expression of SHP2 in colorectal cancer (CRC) may be associated with prognosis. However, validation with large sample data is lacking. Materials and Methods: Tissue microarrays containing 860 CRCs and 197 mucosal tissues adjacent to the tumors were constructed. Immunohistochemistry was used to evaluate the expression of SHP2. Differences between SHP2 expression and clinicopathological parameters were evaluated. Kaplan-Meier survival curves and log-rank tests were used to analyze the relationships between SHP2 expression and the overall survival of patients. A Cox proportional hazard regression model was used for univariate and multivariate analyses of prognostic factors., Results: SHP2 expression in CRCs tissues was significantly higher than those in adjacent mucosal tissues (P < 0.001). SHP2 expression was related to tumor differentiation, depth of invasion, distant metastasis, vascular tumor thrombus, lymph node metastasis, and TNM classification (P < 0.05). The prognosis of the high-expression group of SHP2 was significantly better than that of the low-expression group (P = 0.008). Univariate analysis showed that the expression of SHP2 was a prognostic factor for CRC (P = 0.008). Multivariate analysis demonstrated that SHP2 remained an independent prognostic factor for CRC (P = 0.033)., Conclusion: The expression of SHP2 was significantly higher in CRC tissues than in adjacent normal tissues. High expression of SHP2 was associated with a promising outcome, suggesting that SHP2 may be a favorable prognostic indicator of CRC.

The tissue microarray (TMA) is a powerful tool for cancer biomarker discovery and validation. Tens to hundreds of samples can be evaluated simultaneously for molecular marker status at the protein or nucleic acid level. Although fully automated or semiautomated technologies for TMA creation provide excellent precision with respect to core transfer, they do not obviate the need for technical expertise to successfully generate high-quality TMA blocks and derivative sections. We have leveraged our expanding bank of formalin-fixed paraffin embedded paired tumor and normal tissues in our academic cancer center to provide a rich source of input material for cancer research TMAs. In this study, we report a stepwise optimization of TMA generation parameters, including paraffin wax selection, tempering protocol, and sectioning conditions, to achieve the best ribbon sectioning. [ABSTRACT FROM AUTHOR]

Background: Matrix metalloproteinases‐20 (MMP20) expression is widely regarded as tooth specific, with expression limited to dental hard tissues. Recently, we reported MMP20 expression and interaction with dentin sialophosphoprotein (DSPP), a member of the Small Integrin Binding Ligand N‐linked Glycoproteins (SIBLINGs), in human oral squamous cell carcinoma (OSCC) and dysplastic oral premalignant lesions (OPLs), suggesting a role for MMP20‐DSPP interaction in oral carcinogenesis. Methods: This study aimed to survey the expression of MMP20 and its cognate DSPP partner in the breast, colon, prostate, thyroid, and cervical neoplasms. Using commercially available tissue microarrays (TMAs) and cell lines, we performed immunohistochemistry, immunofluorescence, proximity ligation assay, and western blot experiments to determine the expressions of MMP20 and DSPP in the breast, colon, prostate, thyroid, cervical neoplasms, and their normal counterparts. Results: Significantly high expression levels of MMP20 and DSPP were observed in the malignant breast, colon, prostate, thyroid, and cervical neoplasms compared with their benign and normal counterparts. Furthermore, MMP20 levels increased with advanced stages of colon and thyroid cancers. DSPP expression increased significantly with tumor stage in all cancers examined. Conclusions: The co‐localization and potential MMP20‐DSPP interaction previously reported in oral cancers are present in other cancers. These results suggest MMP20‐DSPP pairing as a potential marker of disease activity in some epithelial cancers with diagnostic and prognostic implications.Our data provide a major reference and baseline document for studies on the role, mechanism, and significance of MMP20‐DSPP expression in major human epithelial neoplasms. In this respect, it is both significant and novel. Furthermore, future findings may offer new opportunities for intervention in epithelial cancers. For example, in cancers in which both MMP20 and its DSPP partner are upregulated, any synthetic MMP protease inhibitor that may be proposed to be used to treat the disorder should first be shown to work in the presence of MMP20 and DSPP. [ABSTRACT FROM AUTHOR]

Abstract Aim Leukocyte-associated immunoglobulin-like receptor-1 (LAIR-1) is an immune inhibitory receptor which is expressed within most types of hematopoietic cells and negatively regulates immune responses. Recently, we found LAIR-1 expression to be present within tumors of nonhematopoietic lineages. However, the roles of LAIR-1 in hepatocellular carcinoma (HCC) have yet to be examined. The purpose of this study was to investigate the expression of LAIR-1 in HCC tissue and assess its clinical significance at this site. Materials and methods Expression levels of LAIR-1 within HCC samples collected from 90 patients and compared with that of slides of normal liver tissue collected from 9 non-HCC patients were measured by immunohistochemistry using tissue microarrays. A semiquantitative score was assigned, as was based on staining intensity and percent of positive cells and a Spearman Rank correlation test was used to assess any potential significant correlations between LAIR-1 expression and clinicopathological factors. Overall survival analysis was performed using the Kaplan-Meier and Log Rank statistical test. Results LAIR-1 expression was detected in cancer tissue and adjacent tumor tissue, but not in normal liver tissue. The percent of LAIR-1-positive expression in cancer tissue of HCC samples was 97.78% (88/90) while that in adjacent tumor tissue was 96.67% (87/90). Significantly greater expression levels of LAIR-1 were obtained from cancer tissue (Mean ± SD = 5.722 ± 2.145) than that in adjacent tumor tissue (4.141 ± 1.486). In addition, LAIR-1 expression was found to be significantly correlated with pathological grade of HCC, T stage, and age. Expression levels of LAIR-1 were related with worse overall survival rates of HCC patients, especially in HCC patients with hepatic cirrhosis. Conclusion Results of this study show that LAIR-1 is expressed in HCC tissues and that high levels of LAIR-1 expression are associated with the poor cancer differentiation. In addition, overexpression of LAIR-1 was significantly associated with worse overall survival in the patients with HCC. These data suggest that LAIR-1 may be an independent predictor for clinical outcomes in patients with HCC. [ABSTRACT FROM AUTHOR]

The tumor microenvironment contributes to the survival and development of tumor cells and is therefore a key target for cancer therapy. The tumor microenvironment has unique physical and chemical properties and is associated with inflammation and immunity. To examine the correlation between tumor microenvironment-associated factors and the efficacy and prognosis of neoadjuvant therapy for rectal cancer, and to compare the differences between two treatments [neoadjuvant chemotherapy (NAC) vs. neoadjuvant chemoradiotherapy (NACR)], an immunohistochemical method was used to measure the expression levels of CD4+ tumor-infiltrating lymphocytes (TILs), cluster of differentiation (CD)8+TILs, forkhead box P3 (FOXP3)+TILs, cytotoxic T lymphocyte-associated antigen-4+TILs and programmed death ligand-1 (PD-L1)+TILs in 109 patients with rectal cancer, pre- and post-neoadjuvant therapy. The significance of these protein expression patterns was also analyzed using tissue microarrays, and the prognostic significance of these findings evaluated. The results indicated that high levels of CD4+TILs, CD8+TILs and PD-L1+TILs may be associated with favorable responses to neoadjuvant therapy, whereas high levels of FOXP3+TILs were associated with poor therapeutic responses. Expression levels of CD8+TILs and FOXP3+TILs following neoadjuvant therapy were independent prognostic factors and affected the total survival of patients subjected to neoadjuvant therapy for the treatment of rectal cancer. Moreover, the effects of NAC and NACR on the tumor microenvironment may be different. [ABSTRACT FROM AUTHOR]

The AIDS and Cancer Specimen Resource (ACSR) has four regional biorepositories (RBRs) in the United States and one in South Africa. The ACSR is funded by the National Cancer Institute (NCI) of the National Institutes of Health (United States) to support investigators studying HIV/AIDS and HIV/AIDS-associated malignancies. The ACSR inventory includes more than 450,000 annotated HIV-positive biospecimens from over 10,000 individuals and 100,000 HIV-negative controls from approximately 4,250 individuals, reflecting the pre-highly active antiretroviral therapy (HAART) and post-HAART era of the HIV epidemic, as well as selected geographic regions heavily impacted by this global pandemic. Funding statement: The U.S. NIH National Cancer Institute has funded the ACSR since 1994. The present award is UM1CA181255.

Head and neck squamous cell carcinoma (HNSCC) is considered as an immunosuppressive disease, with impaired tumor-infiltrating T lymphocytes and increased suppressive immune cells. The efficacy of CD47 antibodies in immune checkpoint therapy is not clearly understood in HNSCC. In this study, human tissue microarrays and immunocompetent transgenic mouse models were used to explore the expression of CD47 and the use of CD47 antibodies in HNSCC. We identified overexpression of CD47 in HNSCC as compared with the control normal human tissue and also in HNSCC mouse models. The expression of CD47 also correlated with clinicopathological parameters as well as outcome. Furthermore, inhibition of CD47 delayed tumor growth and improved tumor microenvironment by stimulating effector T cells and decreasing suppressive immune cells and regulating the function of CD11b+ Ly6G+ MDSC. Our data suggest that CD47 blockade may be a potential immunotherapeutic target in human HNSCC.

Whilst automated analysis of immunostains in pathology research has focused predominantly on the epithelial compartment, automated analysis of stains in the stromal compartment is challenging and therefore requires time-consuming pathological input and guidance to adjust to tissue morphometry as perceived by pathologists. This study aimed to develop a robust method to automate stromal stain analyses using 2 of the commonest stromal stains (SMA and desmin) employed in clinical pathology practice as examples. An effective computational method capable of automatically assessing and quantifying tumour-associated stromal stains was developed and applied on cores of colorectal cancer tissue microarrays. The methodology combines both mathematical models and deep learning techniques with the former requiring no training data and the latter as many inputs as possible. The novel mathematical model was used to produce a digital double marker overlay allowing for fast automated digital multiplex analysis of stromal stains. The results show that deep learning methodologies in combination with mathematical modelling allow for an accurate means of quantifying stromal stains whilst also opening up new possibilities of digital multiplex analyses., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

Objective This study was undertaken primarily to research transforming growth factor β1 (TGF-β1) and Wnt inhibitory factor 1 (WIF1) for the prediction of nonfunctioning pituitary adenoma (NFPAs) invasion and recurrence of tumor samples and the relations between quantitatively determined markers and clinical characters. Methods We studied 104 patients, including 59 patients without recurrence and 45 patients with recurrence (9 patients with one surgery and 36 patients operated twice, both tumors being studied). All tissues were immunostained for TGF-β1 and WIF1 using tissue microarrays and confirmed with real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Western blot. Results We found that invasion, TGF-β1, and WIF1 were significantly associated with recurrence and that age was associated with low expression of TGF-β1 and WIF1 (P < 0.001). There were no statistically significant differences in the expression of the 2 proteins between the noninvasive and the invasive groups. The expression of TGF-β1 and WIF1 in primary tumors in the recurrence group was lower than in the nonrecurrence group (P < 0.001). In the 36 paired primary or recurrent tumors, the expression of TGF-β1 and WIF1 in recurrent tumors was higher than the expression of primary tumors, which was confirmed with qRT-PCR and Western blot. Therefore, TGF-β1 and WIF1 seem to be related to recurrence or progression of pituitary adenomas. Conclusions The expression of TGF-β1 and WIF1 in NFPAs correlated with cell proliferation and recurrence potential. They may be good markers of progressive behavior in NFPAs; however, the biologic mechanism needs further study. Highlights • This study involved 36 paired primary/recurrent NFPAs and evaluate the expression of TGF-β1 and WIF1 in this respect. • They may be good markers of progressive behavior in NFPAs. However, the biologic mechanism still needs further study. • Age was associated with the expression of WIF1 and TGF-β1. [ABSTRACT FROM AUTHOR]

The AIDS and Cancer Specimen Resource (ACSR) has four regional biorepositories (RBRs) in the United States and one in South Africa. The ACSR is funded by the National Cancer Institute (NCI) of the National Institutes of Health (United States) to support investigators studying HIV/AIDS and HIV/AIDS-associated malignancies. The ACSR inventory includes more than 450,000 annotated HIV-positive biospecimens from over 10,000 individuals and 100,000 HIV-negative controls from approximately 4,250 individuals, reflecting the pre-highly active antiretroviral therapy (HAART) and post-HAART era of the HIV epidemic, as well as selected geographic regions heavily impacted by this global pandemic. [ABSTRACT FROM AUTHOR]

High expression of S‑phase kinase associated protein 2 (Skp2) is associated with numerous clinicopathological parameters, including histology, lymph node metastasis, smoking status, differentiation and Tumor‑Node‑Metastasis stage in non‑small cell lung cancer (NSCLC). Skp2 protein is overexpressed in lung squamous cell carcinoma (LUSC), compared with lung adenocarcinoma (LUAD), whilst the clinicopathological and prognostic implications in LUAD or LUSC remain unclear. A larger study is required to assess the differences in Skp2 expression between these NSCLC types. In the present study, the clinicopathological features and immunohistochemical expression of the Skp2 protein were studied in 500 patients with NSCLC (351 with LUAD and 149 with LUSC). Survival analyses were performed using Kaplan‑Meier method and Cox regression model. Skp2 associated genes were identified based on the data from The Cancer Genome Atlas database. Skp2 was overexpressed in patients with LUSC, compared with LUAD (P<0.001). In histology subgroup analysis, differences in Skp2 protein expression were observed in patients with LUAD, based on sex, differentiation, smoking history, stage, lymph node metastasis and tumor diameter (P<0.05), but not in patients with LUSC except for smoking status. High Skp2 protein expression in patients with LUAD was associated with reduced overall survival (OS; P<0.001), but not in patients with LUSC (P=0.686). The multivariate analysis demonstrated that Skp2 expression is an independent unfavorable prognostic factor for OS in patients with LUAD (RR=1.845, P<0.05). Bioinformatics analyses revealed that minichromosome maintenance complex component 2, cell division cycle 45, replication factor C subunit 4, which are differently expressed in LUAD and LUSC, are associated with Skp2 expression and participate in DNA replication and G1/S transition. Skp2 protein expression differs in LUAD and LUSC. The clinicopathological and prognostic implications based on Skp2 expression in LUAD and LUSC should be considered different. LUSC with high Skp2 expression may have robust proliferation ability. [ABSTRACT FROM AUTHOR]