BackgroundCell-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.ResultsThe 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.ConclusionsOur 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.
BackgroundCurrent next-generation sequencing (NGS) platforms adopt two types of sequencing mechanisms: by synthesis or by ligation. The former is employed by 454 and Solexa systems, while the latter by SOLiD system. Although the pros and cons for each sequencing mechanism have more or less been discussed in a number of occasions, the potential obstacle imposed by palindromic sequences has not yet been addressed.MethodsTo test the effect of the palindromic region on sequencing efficacy, we clonally amplified a paired-end ditag sequence composed of a 24-bp palindromic sequence flanked by a pair of tags from the E. coli genome. We used the near homogeneous fragments produced from MmeI digestion of the amplified clone to generate a sequencing library for SOLiD 5500xl sequencer.ResultsResults showed that, traditional ABI sequencers, which adopt sequencing-by-synthesis mechanism, were able to read through the palindromic region. However, SOLiD 5500xl was unable to do so. Instead, the palindromic region was read as miscellaneous random sequences. Moreover, readable tag sequence turned obscure ~2 bp prior to the palindromic region.ConclusionsTaken together, we demonstrate that SOLiD machines, which employ sequencing-by-ligation mechanism, are unable to read through the palindromic region. On the other hand, sequencing-by-synthesis sequencers had no difficulty in doing so.
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.
Single cell transcriptome (SCT) analysis provides superior resolution to illustrate tumor cell heterogeneity for clinical implications. We characterized four SCTs of MCF-7 using 143 housekeeping genes (HKGs) as control, of which lactate dehydrogenase B (LDHB) expression is silenced. These SCT libraries mapped to 11,423, 11,486, 10,380, and 11,306 RefSeq genes (UCSC), respectively. High consistency in HKG expression levels across all four SCTs, along with transcriptional silencing of LDHB, was observed, suggesting a high sensitivity and reproducibility of the SCT analysis. Cross-library comparison on expression levels by scatter plotting revealed a linear correlation and an 83–94% overlap in transcript isoforms and expressed genes were also observed. To gain insight of transcriptional diversity among the SCTs, expressed genes were split into consistently expressed (CE) (expressed in all SCTs) and inconsistently expressed (IE) (expressed in some but not all SCTs) genes for further characterization, along with the 142 expressed HKGs as a reference. Distinct transcriptional strengths were found among these groups, with averages of 1,612.0, 88.0 and 1.2 FPKM for HKGs, CE and IE, respectively. Comparison between CE and IE groups further indicated that expressions of CE genes vary more significantly than that of IE genes. Gene Ontology analysis indicated that proteins encoded by CE genes are mainly involved in fundamental intracellular activities, while proteins encoded by IE genes are mainly for extracellular activities, especially acting as receptors or ion channels. The diversified gene expressions, especially for those encoded by IE genes, may contribute to cancer drug resistance.
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