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Early onset breast cancer (EOBC), diagnosed at age ~40 or younger, is associated with a poorer prognosis and higher mortality rate compared to breast cancer diagnosed at age 50 or older. EOBC poses a serious threat to public health and requires in-depth investigation. We studied a cohort comprising 90 Taiwanese female patients, aiming to unravel the underlying mechanisms of EOBC etiopathogenesis. Sequence data generated by whole-exome sequencing (WES) and whole-genome sequencing (WGS) from white blood cell (WBC)-tumor pairs were analyzed to identify somatic missense mutations, copy number variations (CNVs) and germline missense mutations. Similar to regular breast cancer, the key somatic mutation-susceptibility genes of EOBC include TP53 (40% prevalence), PIK3CA (37%), GATA3 (17%) and KMT2C (17%), which are frequently reported in breast cancer; however, the structural protein-coding genes MUC17 (19%), FLG (16%) and NEBL (11%) show a significantly higher prevalence in EOBC. Furthermore, the top 2 genes harboring EOBC germline mutations, MUC16 (19%) and KRT18 (19%), encode structural proteins. Compared to conventional breast cancer, an unexpectedly higher number of EOBC susceptibility genes encode structural proteins. We suspect that mutations in structural proteins may increase physical permeability to environmental hormones and carcinogens and cause breast cancer to occur at a young age.

BACKGROUND:Cell-free circulating DNA (cfDNA) is becoming a useful biopsy for noninvasive diagnosis of diseases. Microbial sequences in plasma cfDNA may provide important information to improve prognosis and treatment. We have developed a stringent method to identify microbial species via microbial cfDNA in the blood plasma of early-onset breast cancer (EOBC) patients and healthy females. Empirically, microbe-originated sequence reads were identified by mapping non-human PE reads in cfDNA libraries to microbial databases. Those mapped concordantly to unique microbial species were assembled into contigs, which were subsequently aligned to the same databases. Microbial species uniquely aligned were identified and compared across all individuals on MCRPM (Microbial CfDNA Reads Per Million quality PE reads) basis. RESULTS:The predominant microbial cfDNAs in all plasma samples examined are originated from bacteria and these bacteria were limited to only a few genera. Among those, Acinetobacter johnsonii XBB1 and low levels of Mycobacterium spp. were commonly found in all healthy females, but also present in an EOBC patient. Compared to those in healthy counterparts, bacterial species in EOBC patients are more diverse and more likely to present at high levels. Among these three EOBC patients tested, a patient who has record high titer (2,724 MCRPM) of Pseudomonas mendocina together with 8.82 MCRPM of Pannonibacter phragmitetus has passed away; another patient infected by multiple Sphingomonas species remains alive; while the third patient who has similar microbial species (Acinetobacter johnsonii XBB1) commonly seen in normal controls is having a normal life. CONCLUSIONS:Our preliminary data on the profiles of microbial cfDNA sequences suggested that it may have some prognostic value in cancer patients. Validation in larger number of patients is warranted.

Abstract Anticancer peptides (ACPs) are a kind of bioactive peptides which could be used as a novel type of anticancer drug that has several advantages over chemistry-based drug, including high specificity, strong tumor penetration capacity, and low toxicity to normal cells. As the number of experimentally verified bioactive peptides has increased significantly, various of in silico approaches are imperative for investigating the characteristics of ACPs. However, the lack of methods for investigating the differences in physicochemical properties of ACPs. In this study, we compared the N- and C-terminal amino acid composition for each peptide, there are three major subtypes of ACPs that are defined based on the distribution of positively charged residues. For the first time, we were motivated to develop a two-step machine learning model for identification of the subtypes of ACPs, which classify the input data into the corresponding group before applying the classifier. Further, to improve the predictive power, the hybrid feature sets were considered for prediction. Evaluation by five-fold cross-validation showed that the two-step model trained with sequence-based features and physicochemical properties was most effective in discriminating between ACPs and non-ACPs. The two-step model trained with the hybrid features performed well, with a sensitivity of 86.75%, a specificity of 85.75%, an accuracy of 86.08%, and a Matthews Correlation Coefficient value of 0.703. Furthermore, the model also consistently provides the effective performance in independent testing set, with sensitivity of 77.6%, specificity of 94.74%, accuracy of 88.99% and the MCC value reached 0.75. Finally, the two-step model has been implemented as a web-based tool, namely iDACP, which is now freely available at http://mer.hc.mmh.org.tw/iDACP/ .

Abstract Background Cell-free circulating DNA (cfDNA) is becoming a useful biopsy for noninvasive diagnosis of diseases. Microbial sequences in plasma cfDNA may provide important information to improve prognosis and treatment. We have developed a stringent method to identify microbial species via microbial cfDNA in the blood plasma of early-onset breast cancer (EOBC) patients and healthy females. Empirically, microbe-originated sequence reads were identified by mapping non-human PE reads in cfDNA libraries to microbial databases. Those mapped concordantly to unique microbial species were assembled into contigs, which were subsequently aligned to the same databases. Microbial species uniquely aligned were identified and compared across all individuals on MCRPM (Microbial CfDNA Reads Per Million quality PE reads) basis. Results The predominant microbial cfDNAs in all plasma samples examined are originated from bacteria and these bacteria were limited to only a few genera. Among those, Acinetobacter johnsonii XBB1 and low levels of Mycobacterium spp. were commonly found in all healthy females, but also present in an EOBC patient. Compared to those in healthy counterparts, bacterial species in EOBC patients are more diverse and more likely to present at high levels. Among these three EOBC patients tested, a patient who has record high titer (2,724 MCRPM) of Pseudomonas mendocina together with 8.82 MCRPM of Pannonibacter phragmitetus has passed away; another patient infected by multiple Sphingomonas species remains alive; while the third patient who has similar microbial species (Acinetobacter johnsonii XBB1) commonly seen in normal controls is having a normal life. Conclusions Our preliminary data on the profiles of microbial cfDNA sequences suggested that it may have some prognostic value in cancer patients. Validation in larger number of patients is warranted.

The IL-6–gp130–STAT3 signaling axis is a major regulator of inflammation. Activating mutations in the gene encoding gp130 and germline gain-of-function mutations in STAT3 (STAT3GOF) are associated with multi-organ autoimmunity, severe morbidity, and adverse prognosis. To dissect crucial cellular subsets and disease biology involved in activated gp130 signaling, the gp130-JAK-STAT3 axis was constitutively activated using a transgene, L-gp130, specifically targeted to T cells. Activating gp130 signaling in T cells in vivo resulted in fatal, early onset, multi-organ autoimmunity in mice that resembled human STAT3GOF disease. Female mice had more rapid disease progression than male mice. On a cellular level, gp130 signaling induced the activation and effector cell differentiation of T cells, promoted the expansion of T helper type 17 (TH17) cells, and impaired the activity of regulatory T cells. Transcriptomic profiling of CD4+ and CD8+ T cells from these mice revealed commonly dysregulated genes and a gene signature that, when applied to human transcriptomic data, improved the segregation of patients with transcriptionally diverse STAT3GOF mutations from healthy controls. The findings demonstrate that increased gp130-STAT3 signaling leads to TH17-driven autoimmunity that phenotypically resembles human STAT3GOF disease. Editor's summary: Gain-of-function mutations in the transcription activator STAT3 cause an autoimmune disease called STAT3GOF syndrome. A challenging feature of this syndrome is the phenotypic heterogeneity of the individual STAT3 mutations. By manipulating an upstream activator instead of STAT3 itself, Baumgartner et al. developed a mouse model that recapitulated more aspects of the disease. Mice with constitutive activation of the cytokine receptor subunit gp130 in T cells developed fatal, multi-organ inflammation with changes in T cell profiles and gene expression that were similar to those in patients with STAT3GOF autoimmunity, suggesting that this model may be useful for investigating the disease and exploring therapeutic options. —Leslie K. Ferrarelli [ABSTRACT FROM AUTHOR]

Primitive neuroectodermal tumor (PNET) is a rare disease and mostly diagnosed in children and young adults. This tumor is presumed to be of neuroectodermal origin, probably developing from migrating embryonic cells of the neural crest. Carcinoembryonic antigen is a glycoprotein and frequently elevated in patients with a variety of epithelial malignancies. We report hereby a 59-year old male patient with pelvic PNET, and the initial presentation was merelyelevating serum CEA of unknown origin. This case might help to support the theory that PNET may have a potential for epithelial or neuroendocrine differentiation.