Fungal mycobiome drives IL-33 secretion and type 2 immunity in pancreatic cancer

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A meta-analysis on salvage surgery as a potentially curative procedure in patients with isolated local recurrent or persistent esophageal cancer after chemoradiotherapy

BackgroundIsolated local recurrent or persistent esophageal cancer (EC) after curative intended definitive (dCRT) or neoadjuvant chemoradiotherapy (nCRT) with initially omitted surgery, is a potential indication for salvage surgery. We aimed to evaluate safety and efficacy of salvage surgery in these patients.Material and methodsA systematic literature search following PRISMA guidelines was performed using databases of PubMed/Medline. All included studies were performed in patients with persistent or recurrent EC after initial treatment with dCRT or nCRT, between 2007 and 2017. Survival analysis was performed with an inverse-variance weighting method.ResultsOf the 278 identified studies, 28 were eligible, including a total of 1076 patients. Postoperative complications after salvage esophagectomy were significantly more common among patients with isolated persistent than in those with locoregional recurrent EC, including respiratory (36.6% versus 22.7%; difference in proportion 10.9 with 95% confidence interval (CI) [3.1; 18.7]) and cardiovascular complications (10.4% versus 4.5%; difference in proportion 5.9 with 95% CI [1.5; 10.2]). The pooled estimated 30- and 90-day mortality was 2.6% [1.6; 3.6] and 8.0% [6.3; 9.8], respectively. The pooled estimated 3-year and 5-year overall survival (OS) were 39.0% (95% CI: [35.8; 42.2]) and 19.4% [95% CI:16.5; 22.4], respectively. Patients with isolated persistent or recurrent EC after initial CRT had similar 5-year OS (14.0% versus 19.7%, difference in proportion −5.7, 95% CI [-13.7; 2.3]).ConclusionsSalvage surgery is a potentially curative procedure in patients with locally recurrent or persistent esophageal cancer and can be performed safely after definitive or neoadjuvant chemoradiotherapy when surgery was initially omitted.     

Preoperative intra-arterial chemotherapy with docetaxel,cisplatin, and peplomycin combined with intravenous chemotherapy using 5-fluorouracil for oral squamous cell carcinoma

The objectives of this study were to evaluate survival in 141 patients with stage II–IV oral squamous cell carcinoma (OSCC) treated with preoperative intra-arterial chemotherapy with docetaxel, cisplatin, and peplomycin combined with intravenous chemotherapy using 5-fluorouracil (IADCPIVF) via the superficial temporal artery, and to clarify the prognostic factors. The study population included 59 patients with stage II OSCC, 34 with stage III, and 48 with stage IV. After IADCPIVF, 139 patients underwent surgery; minimally invasive surgeries (MIS) including excisional biopsy were performed on 96 patients with a remarkably good response to IADCPIVF. The primary tumour response rate was 99.3% (complete response rate 56.7%, good partial response rate 17.0%, fair partial response rate 25.5%). Additionally, there were no serious adverse events associated with IADCPIVF. The 5-year overall survival rate was 74.6% (stage II 83.6%, stage III 72.7%, stage IV 64.8%). In the multivariate analysis of survival, T classification and clinical tumour response were significant prognostic factors. Eight (8.3%) of the patients who received MIS had primary recurrence and six were salvaged. In conclusion, IADCPIVF is safe and efficacious for treating OSCC, and MIS could reduce the extent of primary tumour resection in the case of a remarkably good response.     

SeqSeg: A sequential method to achieve nasopharyngeal carcinoma segmentation free from background dominance

Reliable nasopharyngeal carcinoma (NPC) segmentation plays an important role in radiotherapy planning. However, recent deep learning methods fail to achieve satisfactory NPC segmentation in magnetic resonance (MR) images, since NPC is infiltrative and typically has a small or even tiny volume with indistinguishable border, making it indiscernible from tightly connected surrounding tissues from immense and complex backgrounds. To address such background dominance problems, this paper proposes a sequential method (SeqSeg) to achieve accurate NPC segmentation. Specifically, the proposed SeqSeg is devoted to solving the problem at two scales: the instance level and feature level. At the instance level, SeqSeg is forced to focus attention on the tumor and its surrounding tissue through the deep Q-learning (DQL)-based NPC detection model by prelocating the tumor and reducing the scale of the segmentation background. Next, at the feature level, SeqSeg uses high-level semantic features in deeper layers to guide feature learning in shallower layers, thus directing the channel-wise and region-wise attention to mine tumor-related features to perform accurate segmentation. The performance of our proposed method is evaluated by extensive experiments on the large NPC dataset containing 1101 patients. The experimental results demonstrated that the proposed SeqSeg not only outperforms several state-of-the-art methods but also achieves better performance in multi-device and multi-center datasets.