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The female breast represents the center of femininity and constitutes one of the most important physical and psychological elements in a woman. It is characterized by a diverse anatomy that comprises different volumes, width, height, projection, composition, shape, and position in the chest wall. Hyman DM, et al. AKT Inhibition in Solid Tumors With AKT1 Mutations. Journal of Clinical Oncology 35, 2251-2259 (2017). After correlating the demographic characteristics (age, weight, BMI, height) with the anthropometric measurements, a positive medium and high correlation was found between weight/BMI and SNN:N, BV and BB. A Low correlation was found between weight/BMI and, ML:N and LBPL. We also found a correlation between age and SSN:N, LBPL, BV and BB. In contrast, no correlation was found between any age and ML:N, or height and any anthropometric measurement ( Table 5). Another clip shows how her bosom makes it difficult for Billie — who goes by @billiebopbillie online — to comfortably fit into a dress. Cytolytic signature (CYT) that measure the activity of lymphocytes T-CD8 to punch the tumoral cells was calculated through a validated gene expression signature based on the geometric mean of normalized gene expression levels of granzyme A (GZMA) and perforin-1 (PRF1) 33. Tumor Inflammation Signature (TIS) score 34, correlated with CD8, CD4, natural Killer and macrophage M2-like activity, was calculated as the average of continuous mean of log2-transformed normalized expression of the identified genes. Individual enrichment scores based on immune-related gene expression signatures 50 were computed with ssGSEA implemented in GSVA v1.36.2 83 Bioconductor library with min gene set size parameter of 5. Wilcoxon test were applied to define significant differences among HM vs. any of the other populations. Statistics

Detected mutations were annotated and classified as driver and passenger somatic mutations using the method implemented in OncodriveMUT algorithm 76 and the Cancer Genome Interpreter ( https://www.cancergenomeinterpreter.org/home) framework, which allows to identify the most likely driver mutations of a tumor. The oncogenic classification: known and predicted mutation (in any neoplasia), were considered as driver alteration and taken into account for analysis. Structural 3D view of AKT1 mutations Mayakonda, A., Lin, D. C., Assenov, Y., Plass, C. & Koeffler, H. P. Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res 28, 1747–1756 (2018). Genomics Laboratory, Red de Apoyo a la Investigación, Universidad Nacional Autónoma de México-Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, México City, México A total of 78 Mexican female volunteers were included for this prospective study. The group was subdivided by decade of life, in 4 groups: third decade (34), fourth decade (21), fifth decade (11), >sixth decade (12).Other potentially novel mutated genes in the HM tumors exhibiting significant mutation prevalence (≥3.0%), non-previously reported in other datasets (Supplementary Data 5), includes MRPL37 and SLC16A8 ( q-value = 2.72E-02 and 1.36E-02, respectively). Although, these novel mutations are predicted to be passenger alterations, most of them have a high deleterious oncogenic capacity and a functional consequence of missense or nonsense change (Supplementary Fig. 7e). Driver and clinically actionable genomic alterations in HM population Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

Li, G. et al. Prevalence and spectrum of AKT1, PIK3CA, PTEN and TP53 somatic mutations in Chinese breast cancer patients. PLoS ONE 13, e0203495 (2018). Banerji, S. et al. Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 486, 405–409 (2012). Of note, when samples are grouped by age, HM patients analyzed did not present statistically significant difference in median TMB values between younger (<45 years old) and older patients, as occurs in tumors from Caucasian and Asian ancestry (TCGA and Japanese dataset) (Fig. 3b) (adjusted p< 0.05). Nor we observed a significant correlation between somatic mutation burden and age in our HM tumor series (Supplementary Fig. 4f). Deciphering mutational signatures Kresovich, J. K. et al. Methylation-based biological age and breast cancer risk. J. Natl Cancer Inst. 111, 1051–1058 (2019). The mean values for Midline to nipple distance divided by age group were: 3rd decade of life (R 9.9 cm, L 10.2 cm), Fourth decade of life (R 10 cm, L 10.4 cm), Fifth decade of life (R 10.4 cm, L 10.9 cm), >6 th decade of life (R 10.5 cm, L 9.8 cm) ( Figure 5). We found a slightly larger midline to nipple distance on the left breasts (R 10.2 cm, L 10.2 cm), nevertheless, this difference is not statistically significant (p < 0.208) ( Table 4).

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Avsar, D.K., Aygit, A.C., Benlier, E., Top, H. and Taskinalp, O. (2010) Anthropometric Breast Measurement: A Study of 385 Turkish Female Students. Aesthetic Surgery Journal/The American Society for Aesthetic Plastic Surgery, 30, 44-50. Measurements were performed in a warm room, using measuring tape, with the subject standing on their feet in a standard anatomical position. With both arms extended to the level of the hips, palms facing forward. Measurements were first taken by the same researcher (DFS) and then confirmed by other two. Hanzelmann, S., Castelo, R. & Guinney, J. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinforma. 14, 7 (2013).

Ciriello, G. et al. Emerging landscape of oncogenic signatures across human cancers. Nat. Genet. 45, 1127–1133 (2013).Whole-exome was captured through Agilent SureSelect ExomePlus bait system (Agilent Technologies, USA) and biotinylated RNA baits 67 process. ~155 Mb baits were target including the standard exome, plus intronic and promoter sequences for known cancer genes, relevant targets identified by cancer genomic studies, TCGA and the Cancer Cell Line Encyclopedia. Exome libraries were sequenced on Illumina GAII or HiSeq 2000 (Illumina, USA) sequencers with 76 base-paired-end reads achieving a mean of 141x. Alignment was performed with the Burrows–Wheeler Alignment tool 68 and standard Picard pipeline to the human genome assembly hg19/GRCh37. Somatic mutation analysis