Multiple bronchiolar adenomas/ciliated muconodular papillary tumors of the bilateral lung with tumor budding and potential malignant transformation into squamous cell carcinoma: a case report and literature review.

Background: Bronchiolar adenoma (BA)/ciliated muconodular papillary tumor (CMPT) is a rare lung tumor characterized by ciliated, mucous and basal cells. Recently, some cases of driver mutations or malignant transformations have been reported. However, the nature of BA/CMPT remains controversial. Here, we report a case of bilateral pulmonary multiple BAs with tumor budding and squamous metaplasia. Case Description: A 55-year-old man presented with multiple small nodules in the lower lobes of the bilateral lungs on physical examination 7 years prior. During the past 3 years of regular follow-up, some nodules had slightly enlarged. Because the nodules were mostly solid, the patient underwent video-assisted thoracoscopic segmentectomy of the left lower lung. A postoperative pathological diagnosis of BA was made. In all lesions, the fusion and mutation of major driver genes were not detected by next-generation sequencing (NGS). No recurrence or metastasis was observed after 37 months of follow-up. Notably, all five resected lesions were BA/CMPT, and one lesion was accompanied by squamous metaplasia and tumor budding. Conclusions: Our report found that BA/CMPT with squamous metaplasia and tumor budding has the potential to transform into lung squamous cell carcinoma, expanding its connection with malignant transformation. Smoking may be one of the risk factors. We also found that BA/CMPT can be multiple lesions rather than a solitary lesion.

A novel PIBF1-RET gene fusion identified from a stage IA lung adenocarcinoma: A case report.

INTRODUCTION: Rearranged during transfection (RET) gene fusions occur in 0.7% to 2% in lung cancer and 1% to 2% in non-small cell lung cancer. Systemic therapies for RET fusion-positive non-small cell lung cancer consist mostly of targeted therapy with RET inhibitors such as selpercatinib and pralsetinib. To date, approximately 40 fusion partners have been reported. Herein, we report a novel progesterone immunomodulatory binding factor 1 (PIBF1)-RET gene fusion identified from a stage IA lung adenocarcinoma and was further validated by RNA sequencing analysis. PATIENT CONCERNS: A 55-year-old male smoker was found by chest computed tomography to have a solid nodule in the right lower lobe of the lung and enlarged mediastinal lymph nodes. DIAGNOSES: The patient was then diagnosed with stage IA lung adenocarcinoma (T1N0M0). INTERVENTION: The patient then underwent thoracoscopic lobectomy of the right lower lobe and mediastinal lymph node dissection. Molecular testing with a targeted panel of 8 lung cancer-associated driver genes detected a novel PIBF1-RET (P16:R12) fusion, which putatively encodes a gene in which the first 16 exons of PIBF1 was concatenated to RET exon 13 and its downstream sequence, retaining the RET kinase domain. The genomic translocation was further validated by RNA sequencing with a panel of 115 cancer-associated genes, which found no other aberrations. OUTCOMES: The patient was discharged 3 days after surgery. CONCLUSION: We report a novel PIBF1-RET fusion in early-stage lung adenocarcinoma. This finding expands the spectrum of RET fusion partners and warrants further studies in characterizing the oncogenic role of this genomic aberration and response to RET-targeted therapies.

Cellular Senescence in Non-Small Cell Lung Cancer.

Lung cancer has the highest mortality rate amongst all malignancies worldwide, and is the second-highest incidence of cancer in women. Non-small cell lung cancer (NSCLC) is responsible for approximately 80% of lung cancer cases. Recent studies indicate that cellular senescence may be a promising cancer biomarker. However, the regulation of cellular senescence and its underlying mechanisms in NSCLC are not yet fully understood. Here, we present a comprehensive analysis of the genes linked to cellular senescence in NSCLC. We also describe the secretory phenotype associated with NSCLC and examine its immune profile and prognostic potential. Our findings offer novel insights into the development of effective NSCLC treatments.

Research progress on the relationship between the TOR signaling pathway regulator, epigenetics, and tumor development.

Almost all cellular activities depend on protein folding, signaling complex assembly/disassembly, and epigenetic regulation. One of the most important regulatory mechanisms responsible for controlling these cellular processes is dynamic protein phosphorylation/dephosphorylation. Alterations in phosphorylation networks have major consequences in the form of disorders, including cancer. Many signaling cascades, including the target of rapamycin (TOR) signaling, are important participants in the cell cycle, and dysregulation in their phosphorylation/dephosphorylation status has been linked to malignancies. As a TOR signaling regulator, protein phosphatase 2A (PP2A) is responsible for most of the phosphatase activities inside the cells. On the other hand, TOR signaling pathway regulator (TIPRL) is an essential PP2A inhibitory protein. Many other physiological roles have also been suggested for TIPRL, such as modulation of TOR pathways, apoptosis, and cell proliferation. It is also reported that TIPRL was increased in various carcinomas, including non-small-cell lung carcinoma (NSCLC) and hepatocellular carcinomas (HCC). Considering the function of PP2A as a tumor suppressor and also the effect of the TIPRL/PP2A axis on apoptosis and proliferation of cancer cells, this review aims to provide a complete view of the role of TIPRL in cancer development in addition to describing TIPRL/PP2A axis and its epigenetic regulation.

An Image-Based Benchmark Dataset and a Novel Object Detector for Water Surface Object Detection.

Water surface object detection is one of the most significant tasks in autonomous driving and water surface vision applications. To date, existing public large-scale datasets collected from websites do not focus on specific scenarios. As a characteristic of these datasets, the quantity of the images and instances is also still at a low level. To accelerate the development of water surface autonomous driving, this paper proposes a large-scale, high-quality annotated benchmark dataset, named Water Surface Object Detection Dataset (WSODD), to benchmark different water surface object detection algorithms. The proposed dataset consists of 7,467 water surface images in different water environments, climate conditions, and shooting times. In addition, the dataset comprises a total of 14 common object categories and 21,911 instances. Simultaneously, more specific scenarios are focused on in WSODD. In order to find a straightforward architecture to provide good performance on WSODD, a new object detector, named CRB-Net, is proposed to serve as a baseline. In experiments, CRB-Net was compared with 16 state-of-the-art object detection methods and outperformed all of them in terms of detection precision. In this paper, we further discuss the effect of the dataset diversity (e.g., instance size, lighting conditions), training set size, and dataset details (e.g., method of categorization). Cross-dataset validation shows that WSODD significantly outperforms other relevant datasets and that the adaptability of CRB-Net is excellent.