According to cisgender respondents, the "preferred" feminine breast has a 45:55 upper-to-lower pole ratio. Preferred breast ratios have not been evaluated for transgender women undergoing breast augmentation. Therefore, this study aimed to determine the preferred breast ratio according to the transgender population and, thus, better inform surgeon planning.

Methods

Patients diagnosed with gender dysphoria were sent a survey with morphed breast images of four different upper-to-lower pole ratios: 35:65, 45:55, 50:50, and 55:45. Respondents ranked the images according to aesthetic preference. Rankings were analyzed by the Condorcet method.

Results

298 survey responses were analyzed: 197 (66.1%) respondents identified as transgender women and 31 (10.4%) as transgender men. Most respondents were younger than 40 (64.8%). Eighty-one (27.2%) had undergone breast augmentation, 136 (45.6%) had not and were not considering it, and 81 (27.2%) had not but were considering it. Across all subgroups, the most preferred ratio was 45:55 (P = 0.046). Those with more masculine genders and assigned female at birth preferred the 45:55 and 50:50 ratios equally. Those in their 30's and younger preferred the 45:55 and 50:50 ratios equally.

Conclusions

The 45:55 ratio, established as the most preferred morphometrics for breast augmentation by cisgender respondents, is also the most aesthetically preferred proportion among transgender patients. Interestingly, the 50:50 ratio, which projects a larger upper bust compared to the 45:55 ratio, may be equally or more appealing to younger patients and those with more masculine genders. We hope these results improve patient-physician shared decision-making and postoperative expectations.

Elucidating antiviral CD8 T lymphocyte responses to SARS-CoV-2 may shed light on the heterogeneity of clinical outcomes and inform vaccine or therapeutic approaches. To facilitate the evaluation of antiviral CD8 T cell responses to SARS-CoV-2, we generated a publicly accessible database of epitopes predicted to bind any class I HLA protein across the entire SARS-CoV-2 proteome. While a subset of epitopes from earlier betacoronaviruses, such as SARS-CoV (SARS), have been validated experimentally, validation systems are often biased toward specific HLA haplotypes (notably HLA-A*02:01) that only account for a fraction of the haplotypes of individuals affected by the SARS-CoV-2 pandemic. To enable evaluation of epitopes across individuals with a variety of HLA haplotypes, we computed the predicted binding affinities between 9-mer peptides derived from the annotated SARS-CoV-2 peptidome across 9,360 MHC class I HLA-A, -B, and -C alleles. There were 6,748 unique combinations of peptides and HLA alleles (pMHCs) with a predicted binding affinity of less than 500nM, including 1,103 unique peptides and 1,022 HLA alleles, spanning 11 annotated superfamilies. These peptides were derived from all 11 proteins spanning the SARS-CoV-2 peptidome, including peptides that have previously been validated experimentally. We also show evidence that these previously validated epitopes may be relevant in other HLA contexts. This complete dataset is available publicly: gs://pici-covid19-data-resources/mhci/peptide_predictions.

Immune checkpoint inhibitors (ICIs), including CTLA-4- and PD-1-blocking antibodies, can have profound effects on tumor immune cell infiltration that have not been consistent in biopsy series reported to date. Here, we analyze seven molecular datasets of samples from patients with advanced melanoma (N = 514) treated with ICI agents to investigate clinical, genomic, and transcriptomic features of anti-PD-1 response in cutaneous melanoma. We find that prior anti-CTLA-4 therapy is associated with differences in genomic, individual gene, and gene signatures in anti-PD-1 responders. Anti-CTLA-4-experienced melanoma tumors that respond to PD-1 blockade exhibit increased tumor mutational burden, inflammatory signatures, and altered cell cycle processes compared with anti-CTLA-4-naive tumors or anti-CTLA-4-experienced, anti-PD-1-nonresponsive melanoma tumors. We report a harmonized, aggregate resource and suggest that prior CTLA-4 blockade therapy is associated with marked differences in the tumor microenvironment that impact the predictive features of PD-1 blockade therapy response.

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community.