Evaluation of pathological response to neoadjuvant chemotherapy in locally advanced cervical cancer.

Neoadjuvant chemotherapy (NACT) is a viable therapeutic option for women diagnosed locally advanced cervical cancer (LACC). However, the factors influencing pathological response are still controversial. We collected pair specimens of 185 LACC patients before and after receiving NACT and conducted histological evaluation. 8 fresh tissues pre-treatment were selected from the entire cohort to conducted immune gene expression profiling. A novel pathological grading system was established by comprehensively assessing the percentages of viable tumor, inflammatory stroma, fibrotic stroma, and necrosis in the tumor bed. Then, 185 patients were categorized into either the good pathological response (GPR) group or the poor pathological response (PPR) group post-NACT, with 134 patients (72.4%, 134/185) achieving GPR. Increasing tumor-infiltrating lymphocytes (TILs) and tumor-infiltrating lymphocytes volume (TILV) pre-treatment were correlated with GPR, with TILV emerging as an independent predictive factor for GPR. Additionally, CIBERSORT analysis revealed noteworthy differences in the expression of immune makers between cPR and non-cPR group. Furthermore, a significantly heightened density of CD8 + T cells and a reduced density of FOXP3 + T cells were observed in GPR than PPR. Importantly, patients exhibiting GPR or inflammatory type demonstrated improved overall survival and disease-free survival. Notably, stromal type was an independent prognostic factor in multivariate analysis. Our study indicates the elevated TILV in pre-treatment specimens may predict a favorable response to NACT, while identifying stromal type in post-treatment specimens as an independent prognostic factor. Moreover, we proposed this pathological grading system in NACT patients, which may offer a more comprehensive understanding of treatment response and prognosis.

A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.

Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathologists. Here we sought to develop and validate a deep learning model capable of precisely distinguishing PCNSL from non-PCNSL lesions, especially glioma, using hematoxylin and eosin (H&E)-stained frozen whole-slide images. Also, we compared its performance against pathologists of varying expertise. Additionally, a human-machine fusion approach integrated both model and pathologic diagnostics. In external cohorts, LGNet achieved AUROCs of 0.965 and 0.972 in distinguishing PCNSL from glioma and AUROCs of 0.981 and 0.993 in differentiating PCNSL from non-PCNSL lesions. Outperforming several pathologists, LGNet significantly improved diagnostic performance, further augmented to some extent by fusion approach. LGNet's proficiency in frozen section analysis and its synergy with pathologists indicate its valuable role in intraoperative diagnosis, particularly in discriminating PCNSL from glioma, alongside other lesions.

Diagnostic utility and sensitivities of matrix Gla protein (MGP), TRPS1 and GATA3 in breast cancer: focusing on metastatic breast cancer, invasive breast carcinoma with special features, and salivary gland-type tumours.

Matrix Gla protein (MGP) and trichorhinophalangeal syndrome type 1 (TRPS1) have recently emerged as novel breast-specific immunohistochemical (IHC) markers, particularly for triple-negative breast cancer (TNBC) and metaplastic carcinoma. The present study aimed to validate and compare the expression of MGP, TRPS1 and GATA binding protein 3 (GATA3) in metastatic breast carcinoma (MBC), invasive breast carcinoma (IBC) with special features, including special types of invasive breast carcinoma (IBC-STs) and invasive breast carcinoma of no special type with unique features, and mammary and non-mammary salivary gland-type tumours (SGTs). Among all enrolled cases, MGP, TRPS1 and GATA3 had comparable high positivity for ER/PR-positive (p=0.148) and HER2-positive (p=0.310) breast carcinoma (BC), while GATA3 positivity was significantly lower in TNBC (p<0.001). Similarly, the positive rates of MGP and TRPS1 in MBCs (99.4%), were higher than in GATA3 (90.9%, p<0.001). Among the IBC-STs, 98.4% of invasive lobular carcinomas (ILCs) were positive for all three markers. Among neuroendocrine tumours (NTs), all cases were positive for TRPS1 and GATA3, while MGP positivity was relatively low (81.8%, p=0.313). In the neuroendocrine carcinoma (NC) subgroup, all cases were positive for GATA3 and MGP, while one case was negative for TRPS1. All carcinomas with apocrine differentiation (APOs) were positive for GATA3 and MGP, while only 60% of the cases demonstrated moderate staining for TRPS1. Among mammary SGTs, MGP demonstrated the highest positivity (100%), followed by TRPS1 (96.0%) and GATA3 (72.0%). Positive staining for these markers was also frequently observed in non-mammary SGTs. Our findings further validate the high sensitivity of MGP and TRPS1 in MBCs, IBC-STs, and breast SGTs. However, none of these markers are capable of distinguishing between mammary and non-mammary SGTs.

Targeting the Cdc2-like kinase 2 for overcoming platinum resistance in ovarian cancer.

Platinum resistance represents a major barrier to the survival of patients with ovarian cancer (OC). Cdc2-like kinase 2 (CLK2) is a major protein kinase associated with oncogenic phenotype and development in some solid tumors. However, the exact role and underlying mechanism of CLK2 in the progression of OC is currently unknown. Using microarray gene expression profiling and immunostaining on OC tissues, we found that CLK2 was upregulated in OC tissues and was associated with a short platinum-free interval in patients. Functional assays showed that CLK2 protected OC cells from platinum-induced apoptosis and allowed tumor xenografts to be more resistant to platinum. Mechanistically, CLK2 phosphorylated breast cancer gene 1 (BRCA1) at serine 1423 (Ser1423) to enhance DNA damage repair, resulting in platinum resistance in OC cells. Meanwhile, in OC cells treated with platinum, p38 stabilized CLK2 protein through phosphorylating at threonine 343 of CLK2. Consequently, the combination of CLK2 and poly ADP-ribose polymerase inhibitors achieved synergistic lethal effect to overcome platinum resistance in patient-derived xenografts, especially those with wild-type BRCA1. These findings provide evidence for a potential strategy to overcome platinum resistance in OC patients by targeting CLK2.

Development and validation of ultrasound-based radiomics model to predict germline BRCA mutations in patients with breast cancer.

BACKGROUND: Identifying breast cancer (BC) patients with germline breast cancer susceptibility gene (gBRCA) mutation is important. The current criteria for germline testing for BC remain controversial. This study aimed to develop a nomogram incorporating ultrasound radiomic features and clinicopathological factors to predict gBRCA mutations in patients with BC. MATERIALS AND METHODS: In this retrospective study, 497 women with BC who underwent gBRCA genetic testing from March 2013 to May 2022 were included, including 348 for training (84 with and 264 without a gBRCA mutation) and 149 for validation(36 patients with and 113 without a gBRCA mutation). Factors associated with gBRCA mutations were identified to establish a clinicopathological model. Radiomics features were extracted from the intratumoral and peritumoral regions (3 mm and 5 mm) of each image. The least absolute shrinkage and selection operator regression algorithm was used to select the features and logistic regression analysis was used to construct three imaging models. Finally, a nomogram that combined clinicopathological and radiomics features was developed. The models were evaluated based on the area under the receiver operating characteristic curve (AUC), calibration, and clinical usefulness. RESULTS: Age at diagnosis, family history of BC, personal history of other BRCA-related cancers, and human epidermal growth factor receptor 2 status were independent predictors of the clinicopathological model. The AUC of the imaging radiomics model combining intratumoral and peritumoral 3 mm areas in the validation set was 0.783 (95% confidence interval [CI]: 0.702-0.862), which showed the best performance among three imaging models. The nomogram yielded better performance than the clinicopathological model in validation sets (AUC: 0.824 [0.755-0.894] versus 0.659 [0.563-0.755], p = 0.007). CONCLUSION: The nomogram based on ultrasound images and clinicopathological factors performs well in predicting gBRCA mutations in BC patients and may help to improve clinical decisions about genetic testing.

The MYBL2-CCL2 axis promotes tumor progression and resistance to anti-PD-1 therapy in ovarian cancer by inducing immunosuppressive macrophages.

BACKGROUND: An immunosuppressive tumor microenvironment in ovarian cancer facilitates tumor progression and resistance to immunotherapy. The function of MYB Proto-Oncogene Like 2 (MYBL2) in the tumor microenvironment remains largely unexplored. METHODS: A syngeneic intraovarian mouse model, flow cytometry analysis, and immunohistochemistry were used to explore the biological function of MYBL2 in tumor progression and immune escape. Molecular and biochemical strategies-namely RNA-sequencing, western blotting, quantitative reverse transcription-polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay, multiplex immunofluorescence, chromatic immunoprecipitation assay (CHIP) and luciferase assay-were used to reveal the mechanisms of MYBL2 in the OVC microenvironment. RESULTS: We found tumor derived MYBL2 indicated poor prognosis and selectively correlated with tumor associated macrophages (TAMs) in ovarian cancer. Mechanically, C-C motif chemokine ligand 2 (CCL2) transcriptionally activated by MYBL2 induced TAMs recruitment and M2-like polarization in vitro. Using a syngeneic intraovarian mouse model, we identified MYBL2 promoted tumor malignancyand increased tumor-infiltrating immunosuppressive macrophages. Cyclin-dependent kinase 2 (CDK2) was a known upstream kinase to phosphorylate MYBL2 and promote its transcriptional function. The upstream inhibitor of CDK2, CVT-313, reprogrammed the tumor microenvironment and reduced anti-PD-1 resistance. CONCLUSIONS: The MYBL2/CCL2 axis contributing to TAMs recruitment and M2-like polarization is crucial to immune evasion and anti-PD-1 resistance in ovarian cancer, which is a potential target to enhance the efficacy of immunotherapy.

Genetic analysis of oligo-recurrence breast cancer: correlation with clinical outcomes.

BACKGROUND: We aimed to identify the relationship between the genomic characteristics and clinical outcomes of oligo-metastatic breast cancer. METHODS: Oligo-metastatic breast cancer diagnosed by pathology from January 2001 and August 2019 were reviewed and we matched the poly-metastatic patients based on the clinicopathological features of patients included. Clinicopathological values and data of genomic alterations were collected. Oligo-recurrence (oligo-R) was defined as a situation where disease progression occurred in less than 5 anatomical sites and other anatomic areas still suppressed by the ongoing therapy. RESULTS: A total of 26 breast cancer patients were enrolled in our study, including 14 patients with strict oligo-metastatic disease (oligo-R > 6 months) and 12 with simultaneous poly-metastatic disease. PIK3CA, TP53 and ERBB2 were the most common shared alterations identified in patients included. Based on the median time of oligo-R, we divided the patients with oligo-metastasis into longer oligo-R group (oligo-R > 31.04 months) and shorter oligo-R group (oligo-R ≤ 31.04 months). The analysis of PIK3CA mutation sites showed that H1047R mutation was closely associated with oligo-metastasis, rather than poly-metastasis. H1047R mutation also predicted a better prognosis (oligo-R > 31.04 months) in oligo-metastatic breast cancer. In addition, HER2 positive was more likely to be related to a good outcome in patients with oligo-metastasis. CONCLUSIONS: Through the genetic analysis of samples from oligo-metastasis, we found the prognostic values of PIK3CA H1047R and HER2 in oligo- and poly-metastasis. We improved the stratification of prognosis and provided new insights for biological behaviors of oligo-metastatic breast cancer.

Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers.

BACKGROUND: For patients with early-stage breast cancers, neoadjuvant treatment is recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish between luminal and non-luminal cancers at early stages will facilitate treatment decisions making. However, the molecular immunohistochemical subtypes based on biopsy specimens are not always consistent with final results based on surgical specimens due to the high intra-tumoral heterogeneity. Given that, we aimed to develop and validate a deep learning radiopathomics (DLRP) model to preoperatively distinguish between luminal and non-luminal breast cancers at early stages based on preoperative ultrasound (US) images, and hematoxylin and eosin (H&E)-stained biopsy slides. METHODS: This multicentre study included three cohorts from a prospective study conducted by our team and registered on the Chinese Clinical Trial Registry (ChiCTR1900027497). Between January 2019 and August 2021, 1809 US images and 603 H&E-stained whole slide images (WSIs) from 603 patients with early-stage breast cancers were obtained. A Resnet18 model pre-trained on ImageNet and a multi-instance learning based attention model were used to extract the features of US and WSIs, respectively. An US-guided Co-Attention module (UCA) was designed for feature fusion of US and WSIs. The DLRP model was constructed based on these three feature sets including deep learning US feature, deep learning WSIs feature and UCA-fused feature from a training cohort (1467 US images and 489 WSIs from 489 patients). The DLRP model's diagnostic performance was validated in an internal validation cohort (342 US images and 114 WSIs from 114 patients) and an external test cohort (270 US images and 90 WSIs from 90 patients). We also compared diagnostic efficacy of the DLRP model with that of deep learning radiomics model and deep learning pathomics model in the external test cohort. FINDINGS: The DLRP yielded high performance with area under the curve (AUC) values of 0.929 (95% CI 0.865-0.968) in the internal validation cohort, and 0.900 (95% CI 0.819-0.953) in the external test cohort. The DLRP also outperformed deep learning radiomics model based on US images only (AUC 0.815 [0.719-0.889], p = 0.027) and deep learning pathomics model based on WSIs only (AUC 0.802 [0.704-0.878], p = 0.013) in the external test cohort. INTERPRETATION: The DLRP can effectively distinguish between luminal and non-luminal breast cancers at early stages before surgery based on pretherapeutic US images and biopsy H&E-stained WSIs, providing a tool to facilitate treatment decision making in early-stage breast cancers. FUNDING: Natural Science Foundation of Guangdong Province (No. 2023A1515011564), and National Natural Science Foundation of China (No. 91959127; No. 81971631).

PD-L1 expression, morphology, and molecular characteristic of a subset of aggressive uterine tumor resembling ovarian sex cord tumor and a literature review.

BACKGROUND: Uterine tumors resembling ovarian sex cord tumor (UTROSCT) is a rare neoplasm of unknown etiology and has undetermined malignant potential. The emergence of recurrent UTROSCT case reports has led to its initial identification as a tumor of low malignancy potential. Owing to its low incidence, we currently lack any in-depth studies regarding the subset of UTROSCTs that may be aggressive in nature. Here, we sought to identify unique characteristics in aggressive UTROSCT. METHODS: 19 cases of UTROSCT were collected. Their histologic and tumor immune microenvironment were evaluated by three gynecologic pathologists. The gene alteration was also detected by RNA sequencing. For later analyses regarding differences between benign and malignant tumors, we supplemented our 19 included cases with additional reports from the literature. RESULTS: Interestingly, we found PD-L1 expression in stromal tumor-infiltrating immune cells (stromal PD-L1) was markedly higher in aggressive UTROSCT. Patients with high stromal PD-L1 (≥ 22.5 cells/mm2) had worse prognosis. When our cases were added with previous cases identified in the literature, we discovered that aggressive UTROSCT was more likely to have significant mitotic activity and NCOA2 gene alterations than benign UTROSCT. Consistence with those results, patients with significant mitotic activity and gene alteration of NCOA2 had worse prognoses. CONCLUSIONS: Collectively, high expression of stromal PD-L1, significant mitotic activity, and gene alteration of NCOA2 may be useful markers to predict aggressive UTROSCT.

Metastasis of breast cancer to bones alters the tumor immune microenvironment.

BACKGROUND: Bone is one of the most frequent sites for breast cancer metastasis. Breast cancer bone metastasis (BCBM) leads to skeletal morbidities including pain, fractures, and spinal compression, all of which severely impact quality of life. Immunotherapy is a promising therapy for patients with advanced cancer, but whether it may provide benefit to metastatic bone cancer is currently unknown. Thus, a better understanding of the immune landscape of bone-disseminated breast cancers may reveal new therapeutic strategies. In this study, we use histopathological analysis to investigate changes within the immune microenvironment of primary breast cancer and paired BCBM. METHODS: Sixty-three patients with BCBM, including 31 with paired primary and bone metastatic lesions, were included in our study. The percentage of stroma and stromal tumor-infiltrating lymphocytes (TILs) was evaluated by histopathological analysis. The quantification of stromal TILs (CD4 + and CD8 +), macrophages (CD68 + and HLA-DR +), programmed cell death protein 1 (PD-1), and programmed cell death protein ligand 1 (PD-L1) was evaluated through immunohistochemical (IHC) staining. Statistical analysis was performed with paired t test, Wilcoxon test, spearman correlation test, and univariate and multivariate cox regression. RESULTS: Median survival after BCBM pathological diagnosis was 20.5 months (range: 3-95 months). Of the immune parameters measured, none correlated with survival after bone metastasis was diagnosed. Compared to the primary site, bone metastases exhibited more tumor stroma (mean: 58.5% vs 28.87%, p < 0.001) and less TILs (mean: 8.45% vs 14.03%, p = 0.042), as determined by H&E analysis. The quantification of primary vs metastatic tissue area with CD4 + (23.95/mm2 vs 51.69/mm2, p = 0.027 and with CD8 + (18.15/mm2 vs 58.95/mm2, p = 0.004) TILs similarly followed this trend and was reduced in number for bone metastases. The number of CD68 + and HLA-DR + macrophages showed no significant difference between primary sites and bone metastases. PD-1 expression was present in 68.25% of the bone metastasis, while PD-L1 expression was only present in 7.94% of the bone metastasis. CONCLUSIONS: Our findings suggest that compared to the primary breast cancer site, bone metastases harbor a less active immune microenvironment. Despite this relatively dampened immune landscape, expression of PD-1 and PD-L1 in the bone metastasis indicates a potential benefit from immune checkpoint inhibitors for some BCBM cases.

Association between Early Immune-Related Adverse Events and Survival in Patients Treated with PD-1/PD-L1 Inhibitors.

BACKGROUND: Immune-related adverse events (irAEs) are side effects that reflect the activation of patients' immune systems after treatment with immune checkpoint inhibitors (ICIs). However, there is no meta-analysis on the effect of early irAEs on patient survival. Thus, we assessed the association between early irAEs and the survival of patients treated with ICIs. METHODS: PubMed, Embase, and Web of Science were searched from May 2010 to May 2020 for all the retrospective and prospective comparative studies to evaluate the hazard ratios (HRs) for death. A random-effects model was used to calculate the pooled HR for death, and heterogeneity was assessed using I² statistics. The main outcomes were overall survival (OS) and progression-free survival (PFS). RESULTS: A total of 11 reports with 2077 patients were included. A significant association was observed between early irAEs and a favorable clinical outcome. Patients with early irAEs had prolonged OS (HR: 0.62, 95% confidence interval (CI): 0.53-0.74, p < 0.001) and PFS (HR: 0.53, 95% CI: 0.41-0.66, p < 0.001) compared to those without; these results were confirmed using a sensitivity analysis. The irAE types, malignancy types, and sample size were correlated with patients' clinical outcomes. CONCLUSIONS: Early irAEs, especially cutaneous irAEs, correlated with a better clinical outcome in patients treated with ICIs.

CMTM6 recruits T cells within the endocervical adenocarcinoma microenvironment and suppresses cell proliferation via the p53 pathway.

Endocervical adenocarcinoma (ECA), harboring poor prognosis, is divided into human papilloma virus (HPV)-associated adenocarcinoma (HPVA) and non-HPVA (NHPVA), each consisting of a heterogeneous immune microenvironment. We aim to examine the effect of CKLF-like MARVEL transmembrane domain 6 (CMTM6), a key regulator of PD-L1, on ECA. Immunohistochemistry and RNA-sequencing (RNA-seq) were used to detect CMTM6, Programmed death ligand 1 (PD-L1), and immune cells biomarkers levels in tumors. RT-qPCR and Western Blotting were used to detect the mRNA and protein level changed in cells. The expression of CMTM6 in ECA is upregulated compared to cervical squamous cell carcinoma tissues. More infiltrating T cells were observed in CMTM6high ECA tissues, especially in CMTM6high HPVA. Higher expression of CMTM6 is associated with a higher rate of infiltrating CD8+ T cells in HPVA, but not in NHPVA. ECA patients were divided into three groups according to the co-expression status of CMTM6 and PD-L1(CPS) . Patients with CMTM6high /PD-L1(CPS+) had the longest OS and DFS, especially in NHPVA patients. Moreover, knock down of CMTM6 promotes ECA cell proliferation via the p53 pathway. CMTM6 recruits T cells, suppresses ECA cell proliferation via the p53 pathway and can be used as a novel prognostic indicator for ECA patients.

Establishment and validation of prognostic nomograms integrating histopathological features in patients with endocervical adenocarcinoma.

AIMS: To develop and verify pathological models using pathological features basing on HE images to predict survival invasive endocervical adenocarcinoma (ECA) postoperatively. METHODS: There are 289 ECA patients were classified into training and validation cohort. A histological signature was produced in 191 patients and verified in the validation groups. Histological models combining the histological features were built, proving the incremental value of our model to the traditional staging system for individualised prognosis estimation. RESULTS: Our model included five chosen histological characteristics and was significantly related to overall survival (OS). Our model had AUC of 0.862 and 0.955, 0.891 and 0.801 in prognosticating 3-year and 5 year OS in the training and validation cohort, respectively. In training cohorts, our model had better performance for evaluation of OS (C-index: 0.832; 95% CI 0.751 to 0.913) than International Federation of Gynecology and Obstetrics (FIGO) staging system (C-index: 0.648; 95% CI 0.542 to 0.753) and treatment (C-index: 0.687; 95% CI 0.605 to 0.769), with advanced efficiency of the classification of survival outcomes. Furthermore, in both cohorts, a risk stratification system was built that was able to precisely stratify stage I and II ECA patients into high-risk and low-risk subpopulation with significantly different prognosis. CONCLUSIONS: A nomogram with five histological signatures had better performance in OS prediction compared with traditional staging systems in ECAs, which might enable a step forward to precision medicine.

Methyltransferase-like 3 promotes cervical cancer metastasis by enhancing cathepsin L mRNA stability in an N6-methyladenosine-dependent manner.

N6-methyladenosine (m6A) is a highly abundant RNA modification in eukaryotic cells. Methyltransferase-like 3 (METTL3), a major protein in the m6A methyltransferase complex, plays important roles in many malignancies, but its role in cervical cancer metastasis remains uncertain. Here, we found that METTL3 was significantly upregulated in cervical cancer tissue, and its upregulation was associated with a poor prognosis in cervical cancer patients. Knockdown of METTL3 significantly reduced cervical cancer cell migration and invasion. Conversely, METTL3 overexpression markedly promoted cervical cancer cell metastasis in vitro and in vivo. Furthermore, METTL3 mediated the m6A modification of cathepsin L (CTSL) mRNA at the 5'-UTR, and the m6A reader protein insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) bound to the m6A sites and enhanced CTSL mRNA stability. Our results indicated that METTL3 enhanced CTSL mRNA stability through an m6A-IGF2BP2-dependent mechanism, thereby promoting cervical cancer cell metastasis. These findings provide insights into a novel m6A modification pattern involved in cervical cancer development.

The prognostic impact of the immune microenvironment in small-cell neuroendocrine carcinoma of the uterine cervix: PD-L1 and immune cell subtypes.

BACKGROUND: We investigate the correlation between programmed cell death-ligand 1 (PD-L1) and tumor-associated immune cell (TAIC) density in small-cell neuroendocrine carcinoma of the uterine cervix (SCNEC) and their correlation with clinicopathologic features. METHODS: PD-L1 and mismatch repair protein (MMR) expression in cancer cells and the density of TAIC were evaluated by immunohistochemistry in 89 SCNEC patients. The combined positive score (CPS), tumor proportion score (TPS), and immune cell score (ICS) of PD-L1 were measured, along with their correlation with clinicopathologic features in SCNEC patients using statistical analyses. RESULTS: CPS of PD-L1 ≥ 1 was seen in 68.5% of patients, positive TPS and ICS of PD-L1 were detected in 59.6% and 33.7% of patients, respectively. PD-L1CPS was higher in tumor-infiltrating immune cells (r = 0.387, p = 0.001) and positively correlated with programmed cell death-1 and forkhead box P3 + regulatory T cell (FOXP3 + Treg) infiltration (r = 0.443, p < 0.001; r = 0.532, p < 0.001). There was no statistical correlation between PD-L1 and MMR status. PD-L1CPS and PD-L1ICS positivity were independent prognostic factors, correlating with a favorable survival (HR (95%CI) = 0.363(0.139-0.950), p = 0.039 and HR (95% CI) = 0.199(0.050-0.802), p = 0.023, respectively). PD-L1ICS positivity was an independent indicator of recurrence in SCNEC patients and associated with better disease-free survival (HR (95% CI) = 0.124(0.036-0425), p = 0.001). TAIC and MMR levels had no statistical impact on survival results. CONCLUSIONS: PD-L1 positivity was seen in over half of SCNEC tumors. It may work synergistically with FOXP3 + Treg and other infiltrating immune cells to support an adaptive immune response. PD-L1 positivity may be a favorable prognostic factor in SCNEC.

Matrix Gla protein (MGP), GATA3, and TRPS1: a novel diagnostic panel to determine breast origin.

BACKGROUND: Metastatic breast carcinoma is commonly considered during differential diagnosis when metastatic disease is detected in females. In addition to the tumor morphology and documented clinical history, sensitive and specific immunohistochemical (IHC) markers such as GCDFP-15, mammaglobin, and GATA3 are helpful for determining breast origin. However, these markers are reported to show lower sensitivity in certain subtypes, such as triple-negative breast cancer (TNBC). MATERIALS AND METHODS: Using bioinformatics analyses, we identified a potential diagnostic panel to determine breast origin: matrix Gla protein (MGP), transcriptional repressor GATA binding 1 (TRPS1), and GATA-binding protein 3 (GATA3). We compared MGP, TRPS1, and GATA3 expression in different subtypes of breast carcinoma of (n = 1201) using IHC. As a newly identified marker, MGP expression was also evaluated in solid tumors (n = 2384) and normal tissues (n = 1351) from different organs. RESULTS: MGP and TRPS1 had comparable positive expression in HER2-positive (91.2% vs. 92.0%, p = 0.79) and TNBC subtypes (87.3% vs. 91.2%, p = 0.18). GATA3 expression was lower than MGP (p < 0.001) or TRPS1 (p < 0.001), especially in HER2-positive (77.0%, p < 0.001) and TNBC (43.3%, p < 0.001) subtypes. TRPS1 had the highest positivity rate (97.9%) in metaplastic TNBCs, followed by MGP (88.6%), while only 47.1% of metaplastic TNBCs were positive for GATA3. When using MGP, GATA3, and TRPS1 as a novel IHC panel, 93.0% of breast carcinomas were positive for at least two markers, and only 9 cases were negative for all three markers. MGP was detected in 36 cases (3.0%) that were negative for both GATA3 and TRPS1. MGP showed mild-to-moderate positive expression in normal hepatocytes, renal tubules, as well as 31.1% (99/318) of hepatocellular carcinomas. Rare cases (0.6-5%) had focal MGP expression in renal, ovarian, lung, urothelial, and cholangiocarcinomas. CONCLUSIONS: Our findings suggest that MGP is a newly identified sensitive IHC marker to support breast origin. MGP, TRPS1, and GATA3 could be applied as a reliable diagnostic panel to determine breast origin in clinical practice.

Immunosuppressive Tumor Microenvironment and Immunotherapy of Epstein-Barr Virus-Associated Malignancies.

The Epstein-Barr virus (EBV) can cause different types of cancer in human beings when the virus infects different cell types with various latent patterns. EBV shapes a distinct and immunosuppressive tumor microenvironment (TME) to its benefit by influencing and interacting with different components in the TME. Different EBV-associated malignancies adopt similar but slightly specific immunosuppressive mechanisms by encoding different EBV products to escape both innate and adaptive immune responses. Strategies reversing the immunosuppressive TME of EBV-associated malignancies have been under evaluation in clinical practice. As the interactions among EBV, tumor cells, and TME are intricate, in this review, we mainly discuss the epidemiology of EBV, the life cycle of EBV, the cellular and molecular composition of TME, and a landscape of different EBV-associated malignancies and immunotherapy by targeting the TME.

A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology.

Epstein-Barr virus-associated gastric cancer (EBVaGC) shows a robust response to immune checkpoint inhibitors. Therefore, a cost-efficient and accessible tool is needed for discriminating EBV status in patients with gastric cancer. Here we introduce a deep convolutional neural network called EBVNet and its fusion with pathologists for predicting EBVaGC from histopathology. The EBVNet yields an averaged area under the receiver operating curve (AUROC) of 0.969 from the internal cross validation, an AUROC of 0.941 on an external dataset from multiple institutes and an AUROC of 0.895 on The Cancer Genome Atlas dataset. The human-machine fusion significantly improves the diagnostic performance of both the EBVNet and the pathologist. This finding suggests that our EBVNet could provide an innovative approach for the identification of EBVaGC and may help effectively select patients with gastric cancer for immunotherapy.

Retraction Notice to: Upregulation of OIP5-AS1 Predicts Poor Prognosis and Contributes to Thyroid Cancer Cell Proliferation and Migration.

[This retracts the article DOI: 10.1016/j.omtn.2019.11.036.].

Tumoral Morphologic Features From Cervical Biopsies That Are Predictive of a Negligible Risk for Nodal Metastasis and Tumor Recurrence in Usual-type Cervical Adenocarcinomas: A Multi-institutional Study.

The metastatic or recurrent potential of localized human papillomavirus-associated endocervical adenocarcinoma (HPVA EAC) is difficult to predict, especially based upon biopsy alone. Recent analyses of small cohorts indicate that high tumor nuclear grade (TNG) and the presence of necrotic tumor debris (NTD) from HPVA EACs in cervical biopsy specimens are highly predictive of nodal metastasis (NM). In the present study, we aimed to investigate how reliably tumoral morphologic features from cervical biopsy specimens predict NM or tumor recurrence (TR) and patient outcomes in a large cohort of endocervical adenocarcinoma patients. A cohort comprised of 397 patients with HPVA EAC treated at 18 institutions was identified, and cervical biopsies were paired with their associated complete tumor resections for a total of 794 specimens. A variety of tumoral histologic features were examined for each paired specimen, including TNG (assessed on a 3-tiered scale of increasing abnormalities-TNG1, TNG2, TNG3) and NTD (defined by the presence of necrotic and apoptotic tumor cells within tumor glandular lumens admixed with granular and eosinophilic amorphous material and inflammatory cells), which were correlated with outcomes. The distribution of TNG in biopsies was as follows: 86 (21.7%) TNG1, 223 (56.2%) TNG2, and 88 (22.2%) TNG3. NTD was identified in 176 (44%) of the biopsy specimens. The sensitivity, specificity, positive predictive value, and negative predictive value of a TNG1 assignment in the biopsy being predictive of the same assignment in the full resection were 0.82 (95% confidence interval [CI]: 0.7-0.9), 0.895 (0.86-0.93), 0.593 (0.48-0.696), and 0.96 (0.94-0.98), respectively. Respective values for an NTD-negative status were 0.89 (95% CI: 0.83-0.92), 0.715 (0.64-0.77), 0.72 (0.65-0.77), and 0.89 (0.83-0.93), respectively. Compared with the other cases in each category, both TNG1 and an NTD-negative status were each significantly associated with lower rates of NM (odds ratio for TNG1=0.245, 95% CI: 0.070-0.857, P=0.0277; for NTD=0.199, 95% CI: 0.094-0.421, P<0.0001) and TR (odds ratio for TNG1=0.225, 95% CI: 0.051-0.987, P=0.0479; for NTD=0.367, 95% CI: 0.171-0.786, P=0.0099) independent of depth of stromal invasion, lymphovascular invasion, tumor size, FIGO stage, and Silva pattern. Overall, 73/379 (19%) cases were both TNG1 and NTD-negative on the biopsy, and none of these 73 cases showed NM (0%), but a single case (1.4%) showed TR. In contrast, among the 324 biopsies with TNG2/3 and/or presence of NTD, 62 (19.1%) had NM, and 41 (12.9%) had TR. In summary, 2 variables in combination (ie, TNG1 and NTD-negative) identified a subset of HPVA EAC patients-∼19%-with a 0% frequency of nodal metastases and only 1.4% frequency of recurrence. Biopsies highly but imperfectly predicted these features. Nonetheless, these findings may potentially be of clinical utility in the risk stratification of patients with HPVA EACs. This may allow some patients with a minimal risk of nodal metastases and TR to be identified at the biopsy phase, thereby facilitating more personalized, possibly less aggressive treatment.