Utility of human epidermal growth factor 2 heterogeneity as a prognostic factor in triple-negative breast cancer.

In some cases of human epidermal growth factor 2 (HER2)-negative breast cancer, including triple-negative breast cancer, HER2 expression is sporadically and strongly upregulated, a condition known as HER2 heterogeneity. We investigated the clinicopathological features of patients with HER2 heterogeneity in triple-negative breast cancers treated with neoadjuvant chemotherapy. Thirty-nine patients with triple-negative breast cancer who had undergone preoperative chemotherapy participated in this study. To assess for HER2 heterogeneity, we used dual in situ hybridization slides. We evaluated the association between HER2 heterogeneity and clinicopathological factors such as rates of pathologic complete response (pCR) and of recurrence-free survival. Of the 39 patients, 15 (38.5%) had cancers with HER2 heterogeneity. The pCR rates were 13.3% among patients with HER2 heterogeneity and 20.8% among those with HER2 nonheterogeneity, but the difference was not significant. The recurrence-free survival rate was significantly lower in patients with HER2 heterogeneity than in those without (P = 0.025). HER2 heterogeneity is a significant predictor of poor prognosis in patients with triple-negative breast cancer treated with neoadjuvant chemotherapy.

Current status and prospects of artificial intelligence in breast cancer pathology: convolutional neural networks to prospective Vision Transformers.

Breast cancer is the most prevalent cancer among women, and its diagnosis requires the accurate identification and classification of histological features for effective patient management. Artificial intelligence, particularly through deep learning, represents the next frontier in cancer diagnosis and management. Notably, the use of convolutional neural networks and emerging Vision Transformers (ViT) has been reported to automate pathologists' tasks, including tumor detection and classification, in addition to improving the efficiency of pathology services. Deep learning applications have also been extended to the prediction of protein expression, molecular subtype, mutation status, therapeutic efficacy, and outcome prediction directly from hematoxylin and eosin-stained slides, bypassing the need for immunohistochemistry or genetic testing. This review explores the current status and prospects of deep learning in breast cancer diagnosis with a focus on whole-slide image analysis. Artificial intelligence applications are increasingly applied to many tasks in breast pathology ranging from disease diagnosis to outcome prediction, thus serving as valuable tools for assisting pathologists and supporting breast cancer management.

Artificial Intelligence-Based Mitosis Scoring in Breast Cancer: Clinical Application.

In recent years, artificial intelligence (AI) has demonstrated exceptional performance in mitosis identification and quantification. However, the implementation of AI in clinical practice needs to be evaluated against the existing methods. This study is aimed at assessing the optimal method of using AI-based mitotic figure scoring in breast cancer (BC). We utilized whole slide images from a large cohort of BC with extended follow-up comprising a discovery (n = 1715) and a validation (n = 859) set (Nottingham cohort). The Cancer Genome Atlas of breast invasive carcinoma (TCGA-BRCA) cohort (n = 757) was used as an external test set. Employing automated mitosis detection, the mitotic count was assessed using 3 different methods, the mitotic count per tumor area (MCT; calculated by dividing the number of mitotic figures by the total tumor area), the mitotic index (MI; defined as the average number of mitotic figures per 1000 malignant cells), and the mitotic activity index (MAI; defined as the number of mitotic figures in 3 mm2 area within the mitotic hotspot). These automated metrics were evaluated and compared based on their correlation with the well-established visual scoring method of the Nottingham grading system and Ki67 score, clinicopathologic parameters, and patient outcomes. AI-based mitotic scores derived from the 3 methods (MCT, MI, and MAI) were significantly correlated with the clinicopathologic characteristics and patient survival (P < .001). However, the mitotic counts and the derived cutoffs varied significantly between the 3 methods. Only MAI and MCT were positively correlated with the gold standard visual scoring method used in Nottingham grading system (r = 0.8 and r = 0.7, respectively) and Ki67 scores (r = 0.69 and r = 0.55, respectively), and MAI was the only independent predictor of survival (P < .05) in multivariate Cox regression analysis. For clinical applications, the optimum method of scoring mitosis using AI needs to be considered. MAI can provide reliable and reproducible results and can accurately quantify mitotic figures in BC.

A case of solitary digital glomus tumor associated with neurofibromatosis type 1.

An association between glomus tumor and neurofibromatosis type 1 has been reported. It is characterized by multiple tumors and young age at onset. The early diagnosis of neurofibromatosis type 1 is important because it is associated with a high rate of malignancy. A 25-year-old man presented to our hospital with left index finger pain that had persisted for 6 years. Physical and imaging findings suggested a benign soft-tissue tumor. Surgery was performed, and the tumor was pathologically diagnosed as glomus tumor. In this case, the patient with a young-onset glomus tumor was suspected of having neurofibromatosis type 1. An additional medical examination led to the diagnosis of unrecognized neurofibromatosis type 1. We experienced a case in which the onset of a glomus tumor led to the diagnosis of neurofibromatosis type 1. Comorbid neurofibromatosis type 1 should be kept in mind when glomus tumors are diagnosed.

Infiltration of Gastric Cancer Stroma by Tumor-Infiltrating Lymphocytes Correlates with Mechanistic Target of Rapamycin Signaling.

INTRODUCTION: We investigated whether the infiltration of tumor-infiltrating lymphocytes (TILs) in gastric cancer (GC), as evaluated by hematoxylin and eosin (H&E) staining, could be a prognostic marker. We also explored on the relationship between TILs and mechanistic target of rapamycin (mTOR) and how it regulates immune effector responses in GC. METHODS: A total of 183 patients with available data on TIL were included. TIL infiltration was evaluated using H&E staining. We also conducted immunohistochemistry to determine mTOR expression. RESULTS: Positive TIL infiltration was defined as TILs ≥20%. There were 72 (39.3%) and 111 (60.7%) positive and negative cases, respectively. TILs positivity significantly correlated with both absence of lymph node metastasis (p = 0.037) and negative p-mTOR expression (p = 0.040). TIL infiltration correlated with a significantly better overall (p = 0.046) and disease-free (p = 0.020) survival. CONCLUSION: mTOR possibly suppresses TIL infiltration in GC. H&E staining is an effective tool for evaluating the immune status of GC patients. H&E staining may be used in clinical practice to monitor treatment response in GC.

Beta-blockade enhances anthracycline control of metastasis in triple-negative breast cancer.

Beta-adrenergic blockade has been associated with improved cancer survival in patients with triple-negative breast cancer (TNBC), but the mechanisms of these effects remain unclear. In clinical epidemiological analyses, we identified a relationship between beta-blocker use and anthracycline chemotherapy in protecting against TNBC progression, disease recurrence, and mortality. We recapitulated the effect of beta-blockade on anthracycline efficacy in xenograft mouse models of TNBC. In metastatic 4T1.2 and MDA-MB-231 mouse models of TNBC, beta-blockade improved the efficacy of the anthracycline doxorubicin by reducing metastatic development. We found that anthracycline chemotherapy alone, in the absence of beta-blockade, increased sympathetic nerve fiber activity and norepinephrine concentration in mammary tumors through the induction of nerve growth factor (NGF) by tumor cells. Moreover, using preclinical models and clinical samples, we found that anthracycline chemotherapy up-regulated ß2-adrenoceptor expression and amplified receptor signaling in tumor cells. Neurotoxin inhibition of sympathetic neural signaling in mammary tumors using 6-hydroxydopamine or genetic deletion of NGF or ß2-adrenoceptor in tumor cells enhanced the therapeutic effect of anthracycline chemotherapy by reducing metastasis in xenograft mouse models. These findings reveal a neuromodulatory effect of anthracycline chemotherapy that undermines its potential therapeutic impact, which can be overcome by inhibiting ß2-adrenergic signaling in the tumor microenvironment. Supplementing anthracycline chemotherapy with adjunctive ß2-adrenergic antagonists represents a potential therapeutic strategy for enhancing the clinical management of TNBC.

Identification of MicroRNAs Associated with Histological Grade in Early-Stage Invasive Breast Cancer.

This study aimed to identify microRNAs associated with histological grade using comprehensive microRNA analysis data obtained by next-generation sequencing from early-stage invasive breast cancer. RNA-seq data from normal breast and breast cancer samples were compared to identify candidate microRNAs with differential expression using bioinformatics. A total of 108 microRNAs were significantly differentially expressed in normal breast and breast cancer tissues. Using clinicopathological information and microRNA sequencing data of 430 patients with breast cancer from The Cancer Genome Atlas (TCGA), the differences in candidate microRNAs between low- and high-grade tumors were identified. Comparing the expression of the 108 microRNAs between low- and high-grade cases, 25 and 18 microRNAs were significantly upregulated and downregulated, respectively, in high-grade cases. Clustering analysis of the TCGA cohort using these 43 microRNAs identified two groups strongly predictive of histological grade. miR-3677 is a microRNA upregulated in high-grade breast cancer. The outcome analysis revealed that patients with high miR-3677 expression had significantly worse prognosis than those with low miR-3677 expression. This study shows that microRNAs are associated with histological grade in early-stage invasive breast cancer. These findings contribute to the elucidation of a new mechanism of breast cancer growth regulated by specific microRNAs.

Association of tumor size in pathological T4 colorectal cancer with desmoplastic reaction and prognosis.

Background: Tumor size in pathological T4 (pT4) colorectal cancer (CRC) is associated with oncological prognosis; however, its relation to epithelial-mesenchymal transition (EMT)-associated histology is unclear. We aimed to investigate the association of tumor size with oncological prognosis and EMT. Methods: We performed a retrospective analysis of 95 patients with primary CRC who underwent radical surgery and were consecutively diagnosed with pT4. Results: Both 3-y disease-free survival (DFS) and cancer-specific survival (CSS) were significantly higher in patients with tumor size ≥50 mm than in those with tumor size <50 mm (P = .009 and P = .011, respectively). The independent factors identified in the multivariate analysis for DFS were pathological lymph node metastasis (hazard ratio [HR], 2.551; 95% confidence interval [CI], 1.031-6.315; P = .043), distant metastasis (HR, 2.511; 95% CI, 1.140-5.532; P = .022), tumor size (HR, 0.462; 95% CI, 0.234-0.913; P = .026), and adjuvant chemotherapy (HR, 0.357; 95% CI, 0.166-0.766; P = .008). The independent factors identified in multivariate analysis for CSS were tumor location (HR, 10.867; 95% CI, 2.539-45.518; P = .001) and tumor size (HR, 0.067; 95% CI, 0.014-0.321; P < .001). In pT4 CRC, smaller tumor size was associated with nonmature desmoplastic reaction and EMT-related histology. Conclusions: Tumor size ≥50 mm was associated with a better DFS and CSS than that of <50 mm, in patients with pT4 CRC. Smaller tumor size with advanced invasion likely reflects a more biologically aggressive phenotype in pT4 CRC.

The frequency and clinical significance of centromere enumeration probe 17 alterations in human epidermal growth factor receptor 2 immunohistochemistry-equivocal invasive breast cancer.

BACKGROUND AND AIMS: Chromosome 17 alterations affect the assessment of HER2 gene amplification in breast cancer (BC), but its clinical significance remains unclear. This study aimed to identify the prevalence of centromere enumeration probe 17 (CEP17) alterations, and its correlation with response to neoadjuvant therapy (NAT) in BC patients with human epidermal growth factor receptor 2 (HER2) immunohistochemistry-equivocal score. METHODS AND RESULTS: A large BC cohort (n = 6049) with HER2 immunohistochemistry score 2+ and florescent in-situ hybridisation (FISH) results was included to assess the prevalence of CEP17 alterations. Another cohort (n = 885) with available clinicopathological data was used to evaluate the effect of CEP17 in the setting of NAT. HER2-amplified tumours with monosomy 17 (CEP17 copy number < 1.5 per nucleus), normal 17 (CEP17 1.5-< 3.0) and polysomy 17 (CEP17 ≥ 3.0) were observed in 16, 59 and 25%, respectively, compared with 3, 74 and 23%, respectively, in HER2-non-amplified tumours. There was no significant relationship between CEP17 alterations and pathological complete response (pCR) rate in both HER2-amplified and HER2-non-amplified tumours. The independent predictors of pCR were oestrogen (ER) negativity in HER2-amplified tumours [ER negative versus positive; odds ratio (OR) = 11.80; 95% confidence interval (CI) = 1.37-102.00; P = 0.02], and histological grade 3 in HER2 non-amplified tumours (3 versus 1, 2; OR = 5.54; 95% CI = 1.61-19.00; P = 0.007). CONCLUSION: The impacts of CEP17 alterations are not as strong as those of HER2/CEP17 ratio and HER2 copy number. The hormonal receptors status and tumour histological grade are more useful to identify BC patients with a HER2 immunohistochemistry-equivocal score who would benefit from NAT.

Association of L-type amino acid transporter 1 (LAT1) with the immune system and prognosis in invasive breast cancer.

L-type amino acid transporter 1 (LAT1), also referred to as SLC7A5, is believed to regulate tumor metabolism and be associated with tumor proliferation. In invasive breast cancer, we clinicopathologically investigated the utility of LAT1 expression. LAT1 expression was evaluated via immunohistochemistry analyses in 250 breast cancer patients undergoing long-term follow-up. We assessed the relationships between LAT1 expression and patient outcomes and clinicopathological factors. Breast cancer-specific survival stratified by LAT1 expression was assessed. Human epidermal growth factor receptor 2 (HER2)-positive patients with metastasis received trastuzumab therapy. The density of tumor-infiltrating lymphocytes (TILs) was evaluated according to the International Working Group guidelines. In the current study, high LAT1 expression was significantly correlated with estrogen receptor (ER) negativity, progesterone receptor negativity, high histological grade, increased TILs, and programmed death ligand 1 positivity. Among the ER-positive and HER2-negative patients, high LAT1 was an independent indicator of poor outcomes (hazard ratio (HR) = 2.97; 95% confidence interval (CI), 1.16-7.62; p = 0.023). Moreover, high LAT1 expression was an independent poor prognostic factor in luminal B-like breast cancer with aggressive features (HR = 3.39; 95% CI 1.35-8.52; p = 0.0094). In conclusion, high LAT1 expression could be used to identify a subgroup of invasive breast cancer characterized by aggressive behavior and high tumor immunoreaction. Our findings suggest that LAT1 might be a candidate therapeutic target for breast cancer patients, particularly those with luminal B-like type breast cancer.

Semantic annotation for computational pathology: multidisciplinary experience and best practice recommendations.

Recent advances in whole-slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence-based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrated solution to utilise information embedded in pathology WSIs beyond what can be obtained through visual assessment. For automated analysis of WSIs and validation of machine learning (ML) models, annotations at the slide, tissue, and cellular levels are required. The annotation of important visual constructs in pathology images is an important component of CPath projects. Improper annotations can result in algorithms that are hard to interpret and can potentially produce inaccurate and inconsistent results. Despite the crucial role of annotations in CPath projects, there are no well-defined guidelines or best practices on how annotations should be carried out. In this paper, we address this shortcoming by presenting the experience and best practices acquired during the execution of a large-scale annotation exercise involving a multidisciplinary team of pathologists, ML experts, and researchers as part of the Pathology image data Lake for Analytics, Knowledge and Education (PathLAKE) consortium. We present a real-world case study along with examples of different types of annotations, diagnostic algorithm, annotation data dictionary, and annotation constructs. The analyses reported in this work highlight best practice recommendations that can be used as annotation guidelines over the lifecycle of a CPath project.

Nuclear morphology in breast lesions: refining its assessment to improve diagnostic concordance.

AIMS: Although evaluation of nuclear morphology is important for the diagnosis and categorisation of breast lesions, the criteria used to assess nuclear atypia rely upon the subjective evaluation of several features that may result in inter- and intraobserver variation. This study aims to refine the definitions of cytonuclear features in various breast lesions. METHODS AND RESULTS: ImageJ was used to assess the nuclear morphological features including nuclear diameter, axis length, perimeter, area, circularity and roundness in 160 breast lesions comprising ductal carcinoma in situ (DCIS), invasive breast carcinoma of no special type (IBC-NST), tubular carcinoma, usual ductal hyperplasia (UDH), columnar cell change (CCC) and flat epithelial atypia (FEA). Reference cells included normal epithelial cells, red blood cells (RBCs) and lymphocytes. Reference cells showed size differences not only between normal epithelial cells and RBCs but also between RBCs in varied-sized blood vessels. Nottingham grade nuclear pleomorphism scores 1 and 3 cut-offs in IBC-NST, compared to normal epithelial cells, were < ×1.2 and > ×1.4 that of mean maximum Feret's diameter and < ×1.6 and > ×2.4 that of mean nuclear area, respectively. Nuclear morphometrics were significantly different in low-grade IBC-NST versus tubular carcinoma, low-grade DCIS versus UDH and CCC versus FEA. No differences in the nuclear features between grade-matched DCIS and IBC-NST were identified. CONCLUSION: This study provides a guide for the assessment of nuclear atypia in breast lesions, refines the comparison with reference cells and highlights the potential diagnostic value of image analysis tools in the era of digital pathology.

Defining the area of mitoses counting in invasive breast cancer using whole slide image.

Although counting mitoses is part of breast cancer grading, concordance studies showed low agreement. Refining the criteria for mitotic counting can improve concordance, particularly when using whole slide images (WSIs). This study aims to refine the methodology for optimal mitoses counting on WSI. Digital images of 595 hematoxylin and eosin stained sections were evaluated. Several morphological criteria were investigated and applied to define mitotic hotspots. Reproducibility, representativeness, time, and association with outcome were the criteria used to evaluate the best area size for mitoses counting. Three approaches for scoring mitoses on WSIs (single and multiple annotated rectangles and multiple digital high-power (×40) screen fields (HPSFs)) were evaluated. The relative increase in tumor cell density was the most significant and easiest parameter for identifying hotspots. Counting mitoses in 3 mm2 area was the most representative regarding saturation and concordance levels. Counting in area <2 mm2 resulted in a significant reduction in mitotic count (P = 0.02), whereas counting in area ≥4 mm2 was time-consuming and did not add a significant rise in overall mitotic count (P = 0.08). Using multiple HPSF, following calibration, provided the most reliable, timesaving, and practical method for mitoses counting on WSI. This study provides evidence-based methodology for defining the area and methodology of visual mitoses counting using WSI. Visual mitoses scoring on WSI can be performed reliably by adjusting the number of monitor screens.

Atypia in breast pathology: what pathologists need to know.

Despite the importance of atypia in diagnosing and classifying breast lesions, the definition of atypia varies depending on the context, with a lack of consistent and objective criteria for assessment. Atypia in breast pathology may be cytonuclear and/or architectural with different applications and implications. Cytonuclear atypia is used to assist the distinction of various intraductal epithelial proliferative lesions including usual ductal hyperplasia (UDH) versus atypical ductal hyperplasia (ADH) or ductal carcinoma in situ (DCIS), and to grade DCIS. In invasive carcinoma, nuclear atypia (i.e., nuclear pleomorphism) is a component of the histological grading system. Stromal cell cytonuclear atypia is one of the key features used to distinguish fibroadenoma from phyllodes tumour (PT) and to classify PT as benign, borderline or malignant. Similarly, cytonuclear atypia is used in the evaluation of myoepithelial cell alterations in the breast. Architectural atypia is used to differentiate flat epithelial atypia (FEA) from ADH or DCIS. In addition to the inherent subjectivity in the interpretation of atypia, which presents as a morphological continuum reflecting a biological spectrum, the lack of standardisation in defining atypia augments diagnostic discordance in breast pathology, with potential implications for patient management. Evidence to date suggests that the traditional criteria used to assess atypia may require modification in the era of digital pathology primary diagnosis. This review aims to provide a comprehensive review of atypia in breast pathology with reference to inconsistencies, challenges and limitations.

Prognostic value of tumor-infiltrating lymphocytes in estrogen receptor-positive and human epidermal growth factor receptor 2-negative breast cancer.

Tumor-infiltrating lymphocytes (TILs) are a significant prognostic factor in triple-negative breast cancer. However, the clinicopathological significance of TILs in estrogen receptor (ER)-positive and human epidermal growth factor receptor 2 (HER2)-negative breast cancer remains unclear. The purpose of the present study was to evaluate the role of TILs in the prognosis of ER-positive and HER2-negative breast cancer. A total of 65 consecutive patients with ER-positive and HER2-negative breast cancer were examined. TILs in stromal tissue (str-TILs) were graded using the International TILs Working Group criteria. The association between several clinicopathological factors and TIL grade were investigated, and the prognostic impact of TILs was compared between luminal A-like and luminal B-like breast cancer. A total of 51 patients (78.5%) had low-grade (0-10%), 11 (16.9%) had intermediate (10-40%) and 3 (4.6%) had high-grade (40-90%) str-TIL levels. There was a significant association between high levels of Ki67 expression and a high str-TIL count. Relapse-free survival was significantly worse in patients with luminal B-like cancer compared with that in patients with luminal A-like cancer. Patients with an intermediate or high str-TIL count had a better prognosis compared with those with a low str-TIL count. All patients with luminal B-like cancer and intermediate or high str-TIL levels developed no recurrence during follow-up. In conclusion, there was a significant correlation between high-grade str-TIL levels and high tumor cell proliferation rate, as well as high levels of Ki67 expression.

Visual assessment of mitotic figures in breast cancer: a comparative study between light microscopy and whole slide images.

BACKGROUND AND AIMS: Visual assessment of mitotic figures in breast cancer (BC) remains a challenge. This is expected to be more pronounced in the digital pathology era. This study aims to refine the criteria of mitotic figure recognition, particularly in whole slide images (WSI). METHOD AND RESULTS: Haematoxylin and eosin (H&E)-stained BC sections (n = 506) were examined using light microscopy (LM) and WSI. A set of features for identifying mitosis in WSI and to distinguish true figures from mimickers was developed. Changes in the mitotic count between the two platforms was explored. Morphological features of mitoses were recorded separately, including absence of nuclear membrane, chromatin hairy-like projections, shape, cytoplasmic features, mitotic cell size and relationship to surrounding cells. Each mitotic phase has its own mimickers. Fifty-eight per cent of mitoses showed absent hairy-like projection in WSI; however, 89% retained their ragged nuclear border, which distinguished them from mimickers including apoptotic cells, lymphocytes and dark elongated hyperchromatic structures. Mitosis in WSI showed loss of fine details, and there was a 20% average reduction rate of mitotic counts when compared to the same area on LM. Using refined mitosis recognition criteria in WSI resulted in a twofold improvement of interobserver concordance. However, when compared to LM, 19% of cases were underscored in WSIs. CONCLUSIONS: All morphological features of mitosis should be considered to enable recognition and differentiation from their mimickers, particularly in WSI, to ensure reliable BC grading. Refining mitotic cut-offs per specific area when using WSI, based on the degree of reduction and association with outcome, is warranted.

Assessment of proliferation in breast cancer: cell cycle or mitosis? An observational study.

BACKGROUND AND AIMS: Proliferation is an important indicator of breast cancer (BC) prognosis, but is assessed using different approaches. Not all cells in the cell cycle are committed to division. This study aimed to characterise quantitative differences between BC cells in the cell cycle and those in mitosis and assess their relationship with other pathological parameters. METHODS AND RESULTS: A cohort of BC sections (n = 621) was stained with haematoxylin and eosin and immunohistochemistry for Ki-67. The proportion of mitotic cells and Ki-67-positive cells was assessed in the same areas. The Cancer Genome Atlas (TCGA) BC cohort was used to assess MKI-67 transcriptome level and its association with the mitotic counts. The mean proportion of BC cells in the cell cycle was 24% (range = 1-90%), while the mean proportion of BC cells in mitosis was 5% (range = 0-73%). A low proportion of mitoses to whole cycling cells was associated with low histological grade tumours and the luminal A molecular subtype, while tumours with a high proportion of mitoses to the overall cycling cells were associated with triple-negative subtype, larger tumour size, grade 3 tumours and lymph node metastasis. The high mitosis/low Ki-67-positive cells tumours showed a significant association with variables of poor prognosis, including high-grade and triple-negative subtypes. CONCLUSION: The proportion of BC cells in the cell cycle and mitosis is variable. We show that not only the number of cells in the cell cycle or mitosis, but also the difference between them, provides valuable information on tumour aggressiveness.

Retrospective observational study of HER2 immunohistochemistry in borderline breast cancer patients undergoing neoadjuvant therapy, with an emphasis on Group 2 (HER2/CEP17 ratio ≥2.0, HER2 copy number <4.0 signals/cell) cases.

BACKGROUND: The ASCO/CAP guidance on HER2 testing in breast cancer (BC) has recently changed. Group 2 tumours with immunohistochemistry score 2+ and HER2/CEP17 ratio ≥2.0 and HER2 copy number <4.0 signals/cell were re-classified as HER2 negative. This study aims to examine the response of Group 2 tumours to neoadjuvant chemotherapy (NACT). METHODS: 749 BC cases were identified from 11 institutions. The association between HER2 groups and pathological complete response (pCR) was assessed. RESULTS: 54% of immunohistochemistry HER2 positive (score 3+) BCs showed pCR, compared to 19% of immunohistochemistry 2+ FISH amplified cases. 27% of Group 2 treated with HER2 targeted therapy achieved pCR, compared to 19 and 11% in the combined Groups 1 + 3 and Groups 4 + 5, respectively. No difference in pCR rates was identified between Group 2 and Group 1 or combined Groups 1 + 3. However, Group 2 response rate was higher than Groups 4 + 5 (p = 0.017). CONCLUSION: No difference in pCR was detected in tumours with a HER2/CEP17 ratio ≥2.0 and a HER2 score 2+ by IHC when stratified by HER2 gene copy number. Our data suggest that ASCO/CAP HER2 Group 2 carcinomas should be evaluated further with respect to eligibility for HER2 targeted therapy.

Low level of stromal lectin-like oxidized LDL receptor 1 and CD8+ cytotoxic T-lymphocytes indicate poor prognosis of colorectal cancer.

BACKGROUND: Lectin-like oxidized LDL receptor-1 (LOX-1) has been identified as a new marker for functional myeloid-derived suppressor cells (MDSCs) that exhibit an immunosuppressive phenotype in the tumor microenvironment (TME). However, the role of LOX-1+ cells in the TME of colorectal cancer (CRC) remains unknown. AIM: This study aimed to determine the expression and significance of LOX-1 in the TME of clinical CRC specimens. METHODS AND RESULTS: We performed immunohistochemical and genetic analyses of LOX-1, CD8, KRAS, and BRAF in 128 resected CRC specimens and determined the expression of IFN-γ and IL-10 using real-time reverse transcription-polymerase chain reaction. We analyzed the correlation between LOX-1, TME factors, gene alteration, clinicopathological factors, and disease prognosis. The co-expression pattern of LOX-1, hematopoietic markers, and a fibroblast marker was evaluated using multiplex immunofluorescence staining. Low stromal LOX-1 expression and low intratumoral CD8+ cytotoxic T-lymphocyte (CTL) status correlated with poor prognosis. Moreover, stromal LOX-1-low/CD8+ CTL-low status was the most important independent prognostic factor of poor overall survival. Most of the LOX-1+ stromal cells were positive for CD163+ , indicating they were CD163+ M2 macrophages. CONCLUSIONS: The MDSC marker, LOX-1, was mainly expressed by M2 macrophages in CRC tissues. LOX-1+ macrophages and CD8+ CTLs may serve as useful biomarkers for predicting the prognosis of CRC.