Prediction of pathologic complete response to neoadjuvant chemoradiation in locally advanced rectal cancer.

Purpose: To investigate the predictive factors of pathologic complete response (pCR) in locally advanced rectal cancer (LARC) patients who had been treated with neoadjuvant chemoradiation (nCRT). Methods and materials: For this retrospective study, 53 LARC patients (37 males and 16 females; age range 25 to 79 years) were selected. Clinical characteristics, baseline mrTNM staging, MR gross tumor volumes (GTV), and pCR were evaluated. The diagnostic accuracy of GTV for predicting pCR was calculated. Results: Among 53 LARC patients, 15 patients achieved pCR (28.3%), while 38 patients achieved non-pCR. Only three (5.7%) out of 53 patients did not downstage after nCRT. GTV and tumor differentiation were the significant prognostic parameters for predicting pCR. A tumor volume threshold of 21.1 cm3 was determined as a predictor for pCR, with a sensitivity of 84% and specificity of 47%. In addition, GTV was associated with mrN stage, circumferential resection margin (CRM) status, extramural vascular invasion (EMVI) status, and pretreatment serum CEA level. Conclusion: Tumor volume and tumor differentiation have significant predictive values in preoperative assessment of pCR among LARC patients. These findings aid clinicians to discriminate those patients who may likely benefit from preoperative regimens and to make optimal treatment plans.

CT-based radiomics signature to predict CD8+ tumor infiltrating lymphocytes in non-small-cell lung cancer.

BACKGROUND: An abundance of CD8+ tumor infiltrating lymphocytes (TILs) in the center of solid tumors is a reliable predictive biomarker for patients eligible for immunotherapy. PURPOSE: To develop a computed tomography (CT)-based radiomics signature for a preoperative prediction of an abundance of CD8+ TILs in non-small-cell lung cancer (NSCLC). MATERIAL AND METHODS: In this retrospective study, 117 consecutive patients with pathologically confirmed NSCLC were included and randomly divided into training (n = 77) and test sets (n = 40). A total of 107 radiomics features were extracted from the three-dimensional volumes of interest of each patient. Least absolute shrinkage and selection operator (LASSO) regression was used to select the strongest features for abundance of CD8+ TILs in NSCLC, and the radiomics score was constructed through a linear combination of these selected features. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive performance of the radiomics score. RESULTS: The radiomics score was associated with an abundance of CD8+ TILs in NSCLC, which achieved an area under the curve (AUC) of 0.83 (95% CI=0.73-0.92) and 0.68 (95% CI=0.54-0.87) in the training and test sets, respectively. The difference was not statistically significant (P = 0.20). The tumors with high CD8+ TILs tended to have heterogeneous dependences (high value of Dependence Non-Uniformity Normalized) and complicated texture (high value of Informational Measure of Correlation 1). CONCLUSION: CT-based radiomics features have the ability to predict CD8+ TILs expression levels of an abundance of CD8+ TILs in NSCLC, which was shown to be a potential imaging biomarker for stratifying patients who may benefit from immunotherapy.

Development and validation of a CT-based nomogram to predict spread through air space (STAS) in peripheral stage IA lung adenocarcinoma.

INTRODUCTION: To develop and validate a simple-to-use nomogram based on preoperative CT to predict spread through air space (STAS) status of stage IA lung adenocarcinoma (ADC). METHODS: In this retrospective study, 434 patients with pathological proven periphery stage IA lung adenocarcinoma were included, which consisted of 349 patients from center I for training group and 85 patients from Center II for test group. STAS was identified in 53 patients (40 patient in the training group and 13 patients in the test group). On the basis of preoperative CT images, 19 morphological characteristics were analyzed. Univariable analysis was used to explore the association between clinical and CT characteristics and STAS status in the training group (P < 0.002). Independent risk factors for STAS were identified using multivariable logistic regression analysis and then used to build a nomogram for preoperative predicting STAS status. RESULTS: Type of nodules, diameter of solid component, lobulation and percentage of the solid component (PSC) were associated with STAS status of peripheral stage IA lung ADCs statistical significantly. Multivariate logistics regression analysis revealed that PSC and lobulation were independent risk factors for STAS. The nomogram based on these factors achieved good predictive performance for STAS with a C-index of 0.803 in the training group and a well-fitted calibration curve. Using a cut-off value which was obtained from Youden index of the receiver operating characteristic (ROC) curve, a diagnosis accuracy of 70.6% was obtained in the test group with sensitivity, specificity, positive prediction value (PPV) and negative prediction value (NPV) of 92.3%, 66.7%, 33.3% and 98.0%, respectively. CONCLUSION: The nomogram based on preoperative CT images could achieve good predictive performance for STAS status of lung adenocarcinomas. This simple-to-used model can facilitate surgeons for a rational operation pattern choice at bedside.

CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. The aims of this study are to develop and validate a computed tomography (CT)­based radiomics model for preoperative prediction of STAS in lung adenocarcinoma. METHODS AND MATERIALS: This retrospective study was approved by an institutional review board and included 462 (mean age, 58.06 years) patients with pathologically confirmed lung adenocarcinoma. STAS was identified in 90 patients (19.5%). Two experienced radiologists segmented and extracted radiomics features on preoperative thin-slice CT images with radiomics extension independently. Intraclass correlation coefficients (ICC) and Pearson's correlation were used to rule out those low reliable (ICC < 0.75) and redundant (r > 0.9) features. Univariate logistic regression was applied to select radiomics features which were associated with STAS. A radiomics-based machine learning predictive model using a random forest (RF) was developed and calibrated with fivefold cross-validation. The diagnostic performance of the model was measured by the area under the curve (AUC) of receiver operating characteristic (ROC). RESULTS: With univariate analysis, 12 radiomics features and age were found to be associated with STAS significantly. The RF model achieved an AUC of 0.754 (a sensitivity of 0.880 and a specificity of 0.588) for predicting STAS. CONCLUSION: CT-based radiomics model can preoperatively predict STAS in lung adenocarcinoma with good diagnosis performance. KEY POINTS: • CT-based radiomics and machine learning model can predict spread through air space (STAS) in lung adenocarcinoma with high accuracy. • The random forest (RF) model achieved an AUC of 0.754 (a sensitivity of 0.880 and a specificity of 0.588) for predicting STAS.

Spatial-Resolution Cell Type Proteome Profiling of Cancer Tissue by Fully Integrated Proteomics Technology.

Increasing attention has been focused on cell type proteome profiling for understanding the heterogeneous multicellular microenvironment in tissue samples. However, current cell type proteome profiling methods need large amounts of starting materials which preclude their application to clinical tumor specimens with limited access. Here, by seamlessly combining laser capture microdissection and integrated proteomics sample preparation technology SISPROT, specific cell types in tumor samples could be precisely dissected with single cell resolution and processed for high-sensitivity proteome profiling. Sample loss and contamination due to the multiple transfer steps are significantly reduced by the full integration and noncontact design. H&E staining dyes which are necessary for cell type investigation could be selectively removed by the unique two-stage design of the spintip device. This easy-to-use proteome profiling technology achieved high sensitivity with the identification of more than 500 proteins from only 0.1 mm2 and 10 µm thickness colon cancer tissue section. The first cell type proteome profiling of four cell types from one colon tumor and surrounding normal tissue, including cancer cells, enterocytes, lymphocytes, and smooth muscle cells, was obtained. 5271, 4691, 4876, and 2140 protein groups were identified, respectively, from tissue section of only 5 mm2 and 10 µm thickness. Furthermore, spatially resolved proteome distribution profiles of enterocytes, lymphocytes, and smooth muscle cells on the same tissue slices and across four consecutive sections with micrometer distance were successfully achieved. This fully integrated proteomics technology, termed LCM-SISPROT, is therefore promising for spatial-resolution cell type proteome profiling of tumor microenvironment with a minute amount of clinical starting materials.

EBV-encoded LMP1 increases nuclear ß-catenin accumulation and its transcriptional activity in nasopharyngeal carcinoma.

This paper aimed to study whether Epstein-Barr virus-encoded latent membrane protein 1 (LMP1) regulates ß-catenin signaling pathway in nasopharyngeal carcinoma (NPC). Western blotting, immunofluorescence, luciferase reporter assay, co-immunoprecipitation assay, and immunohistochemistry staining were used. LMP1 increased ß-catenin transcriptional activity in NPC cell lines. The upregulation of ß-catenin transcriptional activity induced by LMP1 was much higher in poorly differentiated NPC cell line CNE2 than that in well-differentiated NPC cell line CNE1. Immunofluorescence staining and Western blotting also showed that LMP1 increased nuclear ß-catenin accumulation in NPC cell lines. Moreover, LMP1 expression was closely related to abnormal ß-catenin expression in NPC tissues by immunohistochemistry. LMP1 may be involved in nasopharyngeal carcinogenesis via ß-catenin signaling pathway.

[Effect of Epstein-Barr virus-encoded latent membrane protein 1 on ß-catenin transcriptional activity and expression in nasopharyngeal carcinoma].

OBJECTIVE: To investigate the contribution of latent membrane protein (LMP)1 to nasopharyngeal carcinogenesis via Wnt/ß-catenin signal pathway. METHODS: The recombinant plasmid pHA2-LMP1 was constructed; immunofluorescence staining, Dual-Luciferase Reporter Assay, Western blot and immunohistochemistry staining were used to study the effect of LMP1 on the transcriptional activity and expression of ß-catenin. RESULTS: (1) Abnormal expression of ß-catenin was obtained in 38 cases (50.7%, 38/75), LMP1 expression was obtained in 38 cases (50.7%, 38/75). There was significantly positive correlation between LMP1 expression and abnormal expression of ß-catenin in nasopharyngeal carcinoma tissue (P = 0.008). (2) The expression of ß-catenin in nuclei of NPC cell line CNE1 and CNE2 transfected with pHA2-LMP1 plasmid dramatically increased, and the expression was remarkable in poorly-differentiated NPC cell line CNE2 than that of well-differentiated CNE1 cells. (3) LMP1 expression dramatically increased the transcriptional activity of ß-catenin in CNE1 and CNE2 cells transfected with pHA2-LMP1 and was in a time-dependent. The transcriptional activity of ß-catenin was higher in poorly-defferentiated cell line CNE2 than that of well-differentiated NPC cell line CNE1. (4) LMP1 expression did not affect the total protein expression level of ß-catenin in both CNE1 and CNE2 cell lines. CONCLUSION: EB virus-encoded LMP1 may be involved in the pathogenesis of NPC via ß-catenin signal pathway.

The association of genomic variation of Epstein-Barr virus BamHI F fragment with the proliferation of nasopharyngeal carcinoma.

To investigate the f variant of Epstein-Barr virus (EBV) in nasopharyngeal carcinogenesis, we detected the f variant in primary nasopharyngeal carcinoma (NPC), metastatic carcinoma of the lymph node (LN), and chronic inflammation of the nasopharynx from the Guangdong region. Meanwhile, we analyzed the relationship between the f variant of EBV and LMP1, Fascin, pStat3, p53, Bcl-2, and Ki-67 expression in NPC. The results showed that the f variant of EBV was found in 11 cases of primary NPCs with LN metastasis, 12 LN metastases, and 18 primary NPCs without LN metastasis. However, only one demonstrated the F/f variant in 50 cases of chronic inflammation of the nasopharynx. The expression rate of LMP1, Fascin, pStat3, p53, Bcl-2, and Ki-67 in NPC with the f or F/f variant was higher than that with the F prototype. Furthermore, there was a significantly positive correlation between the f variant of EBV and Ki-67 expression (p < 0.05). Our study suggests that the f variant of EBV may be closely related to nasopharyngeal carcinogenesis.

[Correlation of Epstein-Barr virus-encoded latent membrane protein 1 (LMP1) to fascin and phosphorylated Stat3 in nasopharyngeal carcinoma].

BACKGROUND & OBJECTIVE: Latent membrane protein 1 (LMP1) of Epstein-Barr (EB) virus is an important oncogene. Fascin is an actin cross-linking protein involved in cell migration and adhesion. Phosphorylated signal transducer and activator of transcription 3 (pStat3) is a member of STATs family, which is closely related to tumorigenesis. This study was to investigate expressions of LMP1, Fascin and pStat3 in nasopharyngeal carcinoma (NPC) tissues and lymph node metastases of NPC, thus to explore their correlations to the initiation and progression of NPC. METHODS: Expressions of EBV-encoded small RNA (EBER), LMP1, Fascin, pStat3, p53, Ki-67 and Bcl-2 were detected in 43 NPC tissues (21 with and 22 without lymph node metastases) and 21 corresponding lymph node metastases using in situ hybridization or immunohistochemistry (IHC). Data were statistically analyzed. Expressions of pStat3 and Fascin were measured in the NPC cell line CNE1 transfected with LMP1-expressing plasmid using Western blot. RESULTS: Positive EBER expression was detected in all 43 NPC tissues and 21 lymph node metastases in NPC. The expression rates of LMP1, Fascin, pStat3, p53, Ki-67, and Bcl-2 were 69.8% (30/43), 93.0% (40/43), 72.1% (31/43), 90.7% (39/43), 88.4% (38/43) and 88.4% (38/43)in 43 NPC tissues, respectively. LMP1 expression was positively correlated with the expression level of Fascin, pStat3, p53, Ki-67 and Bcl-2 in 43 NPC cases(P < 0.05). LMP1 was found in 10 out of 21 (46.7%) lymph node metastases in NPC. In addition, LMP1 expression dramatically increased pStat3 and Fascin in CNE1 cells. CONCLUSIONS: LMP1 is expressed in lymph node metastatases in NPC. The expression of LMP1 is positively correlated with Fascin, pStat3 and the proliferation index of tumor cells. Moreover, LMP1 up-regulates pStat3 and Fascin in NPC cells.

[Analysis of Epstein-Barr virus BamH I "f" variant in nodal metastasis of nasopharyngeal carcinoma].

OBJECTIVE: To investigate the Epstein-Barr virus (EBV) BamH I "f" variant in primary nasopharyngeal carcinoma (NPC) and its metastases in lymph nodes (LN). METHODS: In situ hybridization was used to detect EBV-encoded small RNA (EBER) expression in 21 paired paraffin-embedded tissue from primary NPC and their lymph node metastases and 22 primary NPC without lymph node metastasis. PCR and restriction fragment length polymorphism (RFLP) assay were used to detect EBV BamH I "f" variant in all cases of NPCs, lymph node metastases and 50 cases of chronic inflammation of nasopharynx from Canton. RESULTS: All cases of NPCs and their lymph node metastases showed EBER expression, indicating a high EBV-positive rate in Cantonese NPC patients. EBV BamH I "f" variant was found in 11 cases (52.4%, 11/21) of primary NPCs with LN metastasis, 12 cases (57.1%, 12/21) of the LN metastases, and 18 cases (81.8%, 18/22) of primary NPCs without LN metastasis. However, of the 50 cases of chronic inflammation of nasopharynx, only one case (2.1%, 1/47) demonstrated BamH I "f" variant. The frequency of BamH I "f" variant in NPC was therefore dramatically higher than that in chronic inflammation of nasopharynx. It is of note that atypical hyperplasia was observed in a few epithelial cells from the case of chronic inflammation of nasopharynx expressing BamH I "f" variant. CONCLUSIONS: The frequency of EBV BamH I "f" variant in NPC is significantly higher than that in chronic inflammation of nasopharynx. It is the first demonstration that the BamH I "f" variant is also present in the LN metastases of NPC. The frequency of BamH I "f" variant in metastatic NPC of the lymph node is almost equal to that of primary NPCs.