Clinical, Pathological, and Genomic profiles of Salivary Warthin tumor-like Mucoepidermoid Carcinoma

Introduction/Objective Warthin tumor-like mucoepidermoid carcinoma(WTL- MEC) is one of the subvariant of mucoepidermoid carcinoma. It mimics the histological features of metaplastic Warthin tumors (mWTs). To investigate the clinicopathological, molecular features, and bio-behaviors of WTL-MEC, we retrospected a cohort of 29 WTL- MEC patients. Methods/Case Report The clinicopathological and microscopic data were collected. Dual-color FISH analysis was performed on paraffin-embedded sections of 29 WTL- MEC patients and 16 mWTs patients using a MAML2 break- apart probe. Whole-exome sequencing and whole transcription sequencing were performed on 3 WTL-MEC and 3 typical mucoepidermoid carcinomas (TMEC) patients. Genetic data were bioinformatically analyzed by software MuTect (v1.7), PINDEL (v0.2.5), SnpEff (v3.0), and etc. Results (if a Case Study enter NA) The cohort of WTL-MEC included 10 male and 19 female patients with a median age of 42.3 years (range, 8 to 68 years). Microscopically, the WTL-MEC lesion consisted of multi-cysts with variant shapes and sizes. The cystic spaces were lined by bi-layered and multilayered oncocytic cells. A transition zone between the bi-layered oncocytic epithelium to the multilayered oncocytic epithelium was observed in WTL-MEC. The cords of epidermoid cells and mucous cells could be found. The germinal center, extensive hyalinization, and mucus extravasation were observed. MAML2 rearrangement was identified in 29 (100%) WTL-MEC. No rearrangement was observed in mWTs by FISH. MET was the most commonly mutated gene in TMEC, and PRDM11 was the most commonly mutated gene in WTL-MEC. Twenty-nine patients were alive without recurrent at the end of the follow-up periods(5–128M). One Patient died due to the metastasis to the lung. Conclusion compared with mWTs, WTL- MEC usually presented in the young, non-smoking female. The histological feature of WTL-MEC depended mainly on the transition zone of the bi-layered oncocytic epithelium and the multilayered oncocytic epithelium. And MAML2 status can confirm the diagnosis. CRTC1-MAML2 and PRDM11 mutations appear to be the main driver event of WTL-MEC. Prognosis was usually favorable, but recurrence or metastasis may rarely occur.

An extended APOBEC3A mutation signature in cancer

APOBEC mutagenesis, a major driver of cancer evolution, is known for targeting TpC sites in DNA. Recently, we showed that APOBEC3A (A3A) targets DNA hairpin loops. Here, we show that DNA secondary structure is in fact an orthogonal influence on A3A substrate optimality and, surprisingly, can override the TpC sequence preference. VpC (non-TpC) sites in optimal hairpins can outperform TpC sites as mutational hotspots. This expanded understanding of APOBEC mutagenesis illuminates the genomic Twin Paradox, a puzzling pattern of closely spaced mutation hotspots in cancer genomes, in which one is a canonical TpC site but the other is a VpC site, and double mutants are seen only in trans, suggesting a two-hit driver event. Our results clarify this paradox, revealing that both hotspots in these twins are optimal A3A substrates. Our findings reshape the notion of a mutation signature, highlighting the additive roles played by DNA sequence and DNA structure.

Inferring parameters of cancer evolution from sequencing and clinical data

As a cancer develops, its cells accrue new mutations, resulting in a heterogeneous, complex genomic profile. We make use of this heterogeneity to derive simple, analytic estimates of parameters driving carcinogenesis and reconstruct the timeline of selective events following initiation of an individual cancer. Using stochastic computer simulations of cancer growth, we show that we can accurately estimate mutation rate, time before and after a driver event occurred, and growth rates of both initiated cancer cells and subsequently appearing subclones. We demonstrate that in order to obtain accurate estimates of mutation rate and timing of events, observed mutation counts should be corrected to account for clonal mutations that occurred after the founding of the tumor, as well as sequencing coverage. We apply our methodology to reconstruct the individual evolutionary histories of chronic lymphocytic leukemia patients. Fitting our model to longitudinal patient data reveals strengths and weaknesses of using an exponential model of cancer growth with constant mutation rate to estimate parameters of cancer evolution.

Driver Mutation Acquisition in Utero and Childhood Followed By Lifelong Clonal Evolution Underlie Myeloproliferative Neoplasms

Background Recurrent mutations in cancer-associated genes drive tumour outgrowth, however, the timing of driver mutations and the dynamics of clonal expansion remain largely unknown. Philadelphia-negative myeloproliferative neoplasms (MPN) are unique cancers capturing the earliest stages of tumorigenesis through to disease evolution. Most patients harbor JAK2V617F, present as the only driver mutation or occurring in combination with driver mutations in genes such as DNMT3A or TET2. We aimed to identify the timing of driver mutations and clonal dynamics in adult MPN. Method We undertook whole-genome sequencing of individual single-cell derived hematopoietic colonies (n=952) together with targeted resequencing of longitudinal blood samples from 10 patients with MPN who presented with disease between ages 20 and 76 years. We identified 448,553 somatic mutations which were used to reconstruct phylogenetic trees of hematopoiesis, tracing blood cell lineages back to embryogenesis. We timed driver mutation acquisition, characterised the dynamics of tumour evolution and measured clonal expansion rates over the lifetime of patients. Resequencing of bulk blood samples corroborated clonal trajectories and provided population estimates. Results JAK2V617F was acquired in utero or childhood in all patients in whom JAK2V617F was the first or the only driver mutation. Earliest age estimates were within a few weeks post conception, and upper estimates of age of acquisition were between 4.1 months and 11.4 years, despite wide ranging ages of MPN presentation. The mean latency between JAK2V617F acquisition and clinical presentation was 34 years (range 20-54 years). Subsequent driver mutation acquisition, including for JAK2V617F, was separated by decades. Disease latency following acquisition of JAK2V617F as a second driver event was still 12-27 years. DNMT3A mutations, commonly associated with age-related clonal hematopoiesis (CH), occurred as the first driver event, subsequent to mutated-JAK2, and as independent clones representing CH in MPN patients. DNMT3A mutations were also first acquired in utero or childhood, at the earliest 1.2 weeks post conception, and the latest 7.9 weeks of gestation to 7.8 years across 4 patients. A recurrent feature of the clonal landscape in MPN was the observation of similar genetic changes repeatedly occurring in unrelated clones within the same patient. Such 'parallel evolution' was observed for chr9p loss-of-heterozygosity, chr1q+ and mutations in myeloid cancer genes, suggesting that patient-specific factors flavour selective landscapes in MPN. Normal hematopoietic stem cells accumulated ~18 somatic mutations/year, however, mutant clones, particularly those with mutant-JAK2, acquired 1.5-5.5 excess mutations/ year and had shorter telomeres, reflecting increased cell divisions during clonal expansion. We modelled the rates of clonal expansion and found that they varied substantially, both across patients and within individuals. In one patient, an in utero acquired DNMT3A-mutated clone expanded slowly at <10%/year, taking 30 years to reach a clonal fraction of 1%, whilst a clone with mutated-JAK2, -DNMT3A and -TET2 expanded at >200%/year, doubling in size every 7 months. JAK2V617F as a single driver mutation also expanded variably across patients, highlighting that other factors, which may include germline, cytokine or stem cell differences between individuals, also influence selection for driver mutations. JAK2V617F associated clonal expansion rates in MPN were greater than that reported for JAK2-CH. Furthermore, rates of expansion in the cohort predicted time to clinical presentation, more so than age of mutation acquisition or tumour burden at diagnosis. This suggests that JAK2-mutant clonal expansion rates determine both if and when clinical manifestations occur. Driver mutations and rates of clonal expansion would have been detectable in blood one to four decades before clinical presentation. Conclusions MPN originate from driver mutation acquisition very early in life, even before birth, with life-long clonal expansion and evolution, establishing a new paradigm for blood cancer development. Early detection of mutant-JAK2 together with determination of clonal expansion rates could provide opportunities for early interventions aimed at minimising thrombotic risk and targeting the mutant clone in at risk individuals. Disclosures No relevant conflicts of interest to declare.