Host Transcriptional Regulatory Genes and Microbiome Networks Crosstalk through Immune Receptors Establishing Normal and Tumor Multiomics Metafirm of the Oral-Gut-Lung Axis.

The microbiome has shown a correlation with the diet and lifestyle of each population in health and disease, the ability to communicate at the cellular level with the host through innate and adaptative immune receptors, and therefore an important role in modulating inflammatory process related to the establishment and progression of cancer. The oral cavity is one of the most important interaction windows between the human body and the environment, allowing the entry of an important number of microorganisms and their passage across the gastrointestinal tract and lungs. In this review, the contribution of the microbiome network to the establishment of systemic diseases like cancer is analyzed through their synergistic interactions and bidirectional crosstalk in the oral-gut-lung axis as well as its communication with the host cells. Moreover, the impact of the characteristic microbiota of each population in the formation of the multiomics molecular metafirm of the oral-gut-lung axis is also analyzed through state-of-the-art sequencing techniques, which allow a global study of the molecular processes involved of the flow of the microbiota environmental signals through cancer-related cells and its relationship with the establishment of the transcription factor network responsible for the control of regulatory processes involved with tumorigenesis.

Multiclass classification of breast cancer histopathology images using multilevel features of deep convolutional neural network.

Breast cancer is a common malignancy and a leading cause of cancer-related deaths in women worldwide. Its early diagnosis can significantly reduce the morbidity and mortality rates in women. To this end, histopathological diagnosis is usually followed as the gold standard approach. However, this process is tedious, labor-intensive, and may be subject to inter-reader variability. Accordingly, an automatic diagnostic system can assist to improve the quality of diagnosis. This paper presents a deep learning approach to automatically classify hematoxylin-eosin-stained breast cancer microscopy images into normal tissue, benign lesion, in situ carcinoma, and invasive carcinoma using our collected dataset. Our proposed model exploited six intermediate layers of the Xception (Extreme Inception) network to retrieve robust and abstract features from input images. First, we optimized the proposed model on the original (unnormalized) dataset using 5-fold cross-validation. Then, we investigated its performance on four normalized datasets resulting from Reinhard, Ruifrok, Macenko, and Vahadane stain normalization. For original images, our proposed framework yielded an accuracy of 98% along with a kappa score of 0.969. Also, it achieved an average AUC-ROC score of 0.998 as well as a mean AUC-PR value of 0.995. Specifically, for in situ carcinoma and invasive carcinoma, it offered sensitivity of 96% and 99%, respectively. For normalized images, the proposed architecture performed better for Makenko normalization compared to the other three techniques. In this case, the proposed model achieved an accuracy of 97.79% together with a kappa score of 0.965. Also, it attained an average AUC-ROC score of 0.997 and a mean AUC-PR value of 0.991. Especially, for in situ carcinoma and invasive carcinoma, it offered sensitivity of 96% and 99%, respectively. These results demonstrate that our proposed model outperformed the baseline AlexNet as well as state-of-the-art VGG16, VGG19, Inception-v3, and Xception models with their default settings. Furthermore, it can be inferred that although stain normalization techniques offered competitive performance, they could not surpass the results of the original dataset.

Exactitud del test ADN-HPV para la detección de la enfermedad cervical de alto grado (NIC 2+) en mujeres con anormalidades citológicas (ASC-US y LSIL), afiliadas a la seguridad social en Bogotá (Colombia) / Accuracy of HPV-DNA test for detecting high-grade disease (CIN 2+)in women with minor cytological abnormalities (ASC-US and LSIL)

Objetivo: evaluar la exactitud de la prueba ADNHPV en el diagnóstico de lesiones premalignas cervicales de alto grado (HSIL, por sus siglas en inglés) en mujeres con alteraciones citológicas ASC-US (células escamosas atípicas de significado indeterminado) y LSIL (lesión escamosa intraepitelial de bajo grado). Metodología: estudio de validez diagnóstica y de cohorte transversal, realizado en mujeres con diagnóstico citológico de ASC-US o LSIL entre octubre de 2006 y enero de 2008, pertenecientes al Programa de Tamizaje de Cáncer de Cérvix de una aseguradora privada en Bogotá (Colombia). Se comparó el resultado de la colposcopia y de la prueba de ADN-HPV con la patología del cérvix como patrón de oro. Resultados: de las 429 mujeres, 344 (80,2%) presentaron ASC-US y 85 (19,8%) LSIL. Las prevalencias de infección por HPV de alto riesgo fueron 52,9% y 75,7% en pacientes con reporte citológico de ASC-US y LSIL, respectivamente. A las 379 de las 425 pacientes se les practicó biopsia, 24 (6,3%) dieron positivas para HSIL. La sensibilidad de la prueba ADN-HPV para detectar lesiones de alto grado (NIC 2+) en las mujeres con reportes de citología ASC-US y LSIL fue 88% y la especificidad fue 44%. En 21 (87.5%) de los 24 casos de HSIL se detectó la presencia de HPV de alto riesgo. Conclusión: debido a que la prueba ADN-HPV tiene una sensibilidad superior a la citología cervicovaginal (CCV), ésta puede considerarse una alternativa útil para estratificar el riesgo y mejorar la aproximación diagnóstica de lesiones premalignas del cuello uterino en mujeres con reporte de ASC-US.

Objective: evaluating the accuracy of the HPV DNA test as a complementary test for diagnosing highgrade cervical disease (high-grade squamous intra epithelia lesions-HSIL) in women with minor cytological abnormalities (atypical squamous cells of undetermined significance ASC-US) and low-grade squamous intraepithelial lesions (LSIL). Methodology: a diagnostic validity study based on a cross-sectional design was applied to 429 women who had had a cytological report of ASC-US and/or LSIL who were attending a health maintenance organisation’s cervical cancer screening programme in Bogotá, Colombia between January 2006 and October 2008. Colposcopy reports and HPV-DNA testresultswerecomparedwithpathologicalreports which were considered the gold standard. Results: 344 (80.2%) of the 429 women had a cytological report of ASC-US and 85 (19.8%) of them one for LSIL. High-risk HPV infection prevalence was 52.9% and 75.7% in patients having an ASC-US and LSIL report, respectively. A biopsy specimen was obtained in 379 of the 429 participants and 24 high-grade cases (6.3%) were diagnosed. DNA-HPV test sensitivity was 88% and specificity was 44% for detecting high-grade disease (CIN 2+) in women having an ASC-US and LSIL cytology report . The presence of high-risk HPV virus was detected in 21 of the 24 HSIL cases (87.5%). Conclusion: the DNA-HPV test’s higher sensitivity compared to the PAP smear (due to high NPV) means that it could be considered a useful tool for stratifying risk and improving the diagnostic approach to premalignant lesions of the uterine cervix in patients having a cytological report of ASC-US.