Relative Convex Hull Determination from Convex Hulls in the Plane

A new algorithm for the determination of the relative convex hull in the plane of a simple polygon A with respect to another simple polygon B which contains A, is proposed. The relative convex hull is also known as geodesic convex hull, and the problem of its determination in the plane is equivalent to find the shortest curve among all Jordan curves lying in the difference set of B and A and encircling A. Algorithms solving this problem known from Computational Geometry are based on the triangulation or similar decomposition of that difference set. The algorithm presented here does not use such decomposition, but it supposes that A and B are given as ordered sequences of vertices. The algorithm is based on convex hull calculations of A and B and of smaller polygons and polylines, it produces the output list of vertices of the relative convex hull from the sequence of vertices of the convex hull of A.Comment: 15 pages, 4 figures, Conference paper published. We corrected two typing errors in Definition 2: $I_S$ has to be defined based on $O_S$, and $I_E$ has to be defined based on $O_E$ (not just using $O$). These errors appeared in the text of the original conference paper, which also contained the pseudocode of an algorithm where $I_S$ and $I_E$ appeared as correctly define

Assessment of the current and emerging criteria for the histopathological classification of lung neuroendocrine tumours in the lungNENomics project

Background: Six thoracic pathologists reviewed 259 lung neuroendocrine tumours (LNETs) from the lungNENomics project, with 171 of them having associated survival data. This cohort presents a unique opportunity to assess the strengths and limitations of current World Health Organization (WHO) classification criteria and to evaluate the utility of emerging markers. Patients and methods: Patients were diagnosed based on the 2021 WHO criteria, with atypical carcinoids (ACs) defined by the presence of focal necrosis and/or 2-10 mitoses per 2 mm2. We investigated two markers of tumour proliferation: the Ki-67 index and phospho-histone H3 (PHH3) protein expression, quantified by pathologists and automatically via deep learning. Additionally, an unsupervised deep learning algorithm was trained to uncover previously unnoticed morphological features with diagnostic value. Results: The accuracy in distinguishing typical from ACs is hampered by interobserver variability in mitotic counting and the limitations of morphological criteria in identifying aggressive cases. Our study reveals that different Ki-67 cut-offs can categorise LNETs similarly to current WHO criteria. Counting mitoses in PHH3+ areas does not improve diagnosis, while providing a similar prognostic value to the current criteria. With the advantage of being time efficient, automated assessment of these markers leads to similar conclusions. Lastly, state-of-the-art deep learning modelling does not uncover undisclosed morphological features with diagnostic value. Conclusions: This study suggests that the mitotic criteria can be complemented by manual or automated assessment of Ki-67 or PHH3 protein expression, but these markers do not significantly improve the prognostic value of the current classification, as the AC group remains highly unspecific for aggressive cases. Therefore, we may have exhausted the potential of morphological features in classifying and prognosticating LNETs. Our study suggests that it might be time to shift the research focus towards investigating molecular markers that could contribute to a more clinically relevant morpho-molecular classification.</p

Phase I study of IMGN901, a CD56-targeting antibody-drug conjugate, in patients with CD56-positive solid tumors.

Background IMGN901 is a CD56-targeting antibody-drug conjugate designed for tumor-selective delivery of the cytotoxic maytansinoid DM1. This phase 1 study investigated the safety, tolerability, pharmacokinetics, and preliminary activity of IMGN901 in patients with CD56-expressing solid tumors. Methods Patients were enrolled in cohorts of escalating IMGN901 doses, administered intravenously, on 3 consecutive days every 21 days. A dose-expansion phase accrued patients with small cell lung cancer (SCLC), Merkel cell carcinoma (MCC), or ovarian cancer. Results Fifty-two patients were treated at doses escalating from 4 to 94 mg/m(2)/day. The maximum tolerated dose (MTD) was determined to be 75 mg/m(2). Dose-limiting toxicities included fatigue, neuropathy, headache or meningitis-like symptoms, chest pain, dyspnea, and myalgias. In the dose-expansion phase (n = 45), seven patients received 75 mg/m(2) and 38 received 60 mg/m(2) for up to 21 cycles. The recommended phase 2 dose (RP2D) was established at 60 mg/m(2) during dose expansion. Overall, treatment-emergent adverse events (TEAEs) were experienced by 96.9 % of all patients, the majority of which were Grade 1 or 2. The most commonly reported Grade 3 or 4 TEAEs were hyponatremia and dyspnea (each 8.2 %). Responses included 1 complete response (CR), 1 clinical CR, and 1 unconfirmed partial response (PR) in MCC; and 1 unconfirmed PR in SCLC. Stable disease was seen for 25 % of all evaluable patients who received doses ≥60 mg/m(2). Conclusions The RP2D for IMGN901 of 60 mg/m(2) administered for 3 consecutive days every 3 weeks was associated with an acceptable tolerability profile. Objective responses were observed in patients with advanced CD56+ cancers

Amplification of telomerase (hTERT) gene is a poor prognostic marker in non-small-cell lung cancer

Telomerase reactivation is a hallmark of human carcinogenesis. Increased telomerase activity may result from gene amplification and/or overexpression. This study evaluates the prognostic value of hTERT gene amplification and mRNA overexpression in 144 resectable non-small-cell lung cancer (NSCLC) specimens. The hTERT gene copy number was assessed by quantitative polymerase chain reaction (qPCR) on laser-capture microdissected tumour cells of 81 tumours, and by fluorescence in situ hybridisation (FISH) on a subset of 59 tumours. hTERT mRNA level was determined by reverse transcription (RT)–qPCR in 130 tumours. In total, 57% of (46 out of 81) primary NSCLC specimens demonstrated hTERT amplification, which was significantly more common (P<0.001) in adenocarcinoma (30 out of 40) than in squamous cell carcinoma (13 out of 37). The hTERT mRNA overexpression was noted in 74% (94 out of 130) of tumours; it was more frequent in squamous cell than in adenocarcinoma (87 vs 68%, P=0.03). Overexpression was significantly associated with amplification (P=0.03), especially in adenocarcinoma. The hTERT gene amplification was prognostic for shorter recurrence-free survival (hazard ratio=2.16, P=0.03). These data indicate that gene amplification is an important mechanism for hTERT overexpression in lung adenocarcinoma and is an independent poor prognostic marker for disease-free survival in NSCLC

VEGFA Upregulates FLJ10540 and Modulates Migration and Invasion of Lung Cancer via PI3K/AKT Pathway

BACKGROUND: Lung adenocarcinoma is the leading cause of cancer-related deaths among both men and women in the world. Despite recent advances in diagnosis and treatment, the mortality rates with an overall 5-year survival of only 15%. This high mortality is probably attributable to early metastasis. Although several well-known markers correlated with poor/metastasis prognosis in lung adenocarcinoma patients by immunohistochemistry was reported, the molecular mechanisms of lung adenocarcinoma development are still not clear. To explore novel molecular markers and their signaling pathways will be crucial for aiding in treatment of lung adenocarcinoma patients. METHODOLOGY/PRINCIPAL FINDINGS: To identify novel lung adenocarcinoma-associated /metastasis genes and to clarify the underlying molecular mechanisms of these targets in lung cancer progression, we created a bioinformatics scheme consisting of integrating three gene expression profile datasets, including pairwise lung adenocarcinoma, secondary metastatic tumors vs. benign tumors, and a series of invasive cell lines. Among the novel targets identified, FLJ10540 was overexpressed in lung cancer tissues and is associated with cell migration and invasion. Furthermore, we employed two co-expression strategies to identify in which pathway FLJ10540 was involved. Lung adenocarcinoma array profiles and tissue microarray IHC staining data showed that FLJ10540 and VEGF-A, as well as FLJ10540 and phospho-AKT exhibit positive correlations, respectively. Stimulation of lung cancer cells with VEGF-A results in an increase in FLJ10540 protein expression and enhances complex formation with PI3K. Treatment with VEGFR2 and PI3K inhibitors affects cell migration and invasion by activating the PI3K/AKT pathway. Moreover, knockdown of FLJ10540 destabilizes formation of the P110-alpha/P85-alpha-(PI3K) complex, further supporting the participation of FLJ10540 in the VEGF-A/PI3K/AKT pathway. CONCLUSIONS/SIGNIFICANCE: This finding set the stage for further testing of FLJ10540 as a new therapeutic target for treating lung cancer and may contribute to the development of new therapeutic strategies that are able to block the PI3K/AKT pathway in lung cancer cells

Constrained distance transforms for spatial atlas registration

BACKGROUND: Spatial frameworks are used to capture organ or whole organism image data in biomedical research. The registration of large biomedical volumetric images is a complex and challenging task, but one that is required for spatially mapped biomedical atlas systems. In most biomedical applications the transforms required are non-rigid and may involve significant deformation relating to variation in pose, natural variation and mutation. Here we develop a new technique to establish such transformations for mapping data that cannot be achieved by existing approaches and that can be used interactively for expert editorial review. RESULTS: This paper presents the Constrained Distance Transform (CDT), a novel method for interactive image registration. The CDT uses radial basis function transforms with distances constrained to geodesics within the domains of the objects being registered. A geodesic distance algorithm is discussed and evaluated. Examples of registration using the CDT are presented. CONCLUSION: The CDT method is shown to be capable of simultaneous registration and foreground segmentation even when very large deformations are required