Concept: Squamous cell carcinoma
MicroRNAs (miRNAs) are endogenous short non-coding RNA molecules that regulate gene expression by repressing translation or cleaving RNA transcripts in a sequence-specific manner. Bioinformatic analyses predict that miRNAs regulate more than 30% of protein coding genes. To date, 1921 human mature miRNAs have been registered in miRBase release 18.0 (http://microrna.sanger.ac.uk/). A growing body of evidence suggests that miRNAs are aberrantly expressed in many human carcinomas and that they play key roles in the initiation, development and metastasis of human cancers, including head and neck squamous cell carcinoma (HNSCC). In this review, eight genome-wide miRNA expression profiles were used to selected aberrantly expressed miRNAs (up-regulated and down-regulated miRNAs) in HNSCC clinical specimens including our miRNA profiles of hypopharyngeal and maxillary sinus squamous cell carcinoma. We discuss recent findings on the aberrant expression of miRNAs and their contribution to human HNSCC oncogenesis.
The taxanes (paclitaxel and docetaxel) represent an important class of antineoplastic agents that interfere with microtubule function leading to altered mitosis and cellular death. Paclitaxel (Taxol(®)) was originally extracted from a yew tree (Taxus spp., Taxaceae) a small slow-growing evergreen, coniferous tree. Due to the initial scarcity of paclitaxel, docetaxel (Taxotere(®)) a semisynthetic analog of paclitaxel produced from the needles of European yew tree, Taxus baccata was developed. Docetaxel differs from paclitaxel in two positions in its chemical structure and this small alteration makes it more water soluble. Today, paclitaxel and docetaxel are widely prescribed antineoplastic agents for a broad range of malignancies including lung cancer, breast cancer, prostate cancer, Kaposi’s sarcoma, squamous cell carcinoma of the head and neck, gastric cancer, esophageal cancer, bladder cancer, and other carcinomas. Although very active clinically, paclitaxel and docetaxel have several clinical problems including poor drug solubility, serious dose-limiting toxicities such as myelosuppression, peripheral sensory neuropathy, allergic reactions, and eventual development of drug resistance. A number of these side effects have been associated with the solvents used for dilution of these antineoplastic agents: Cremophor EL for paclitaxel and polysorbate 80 for docetaxel. In addition, reports have linked these solvents to the alterations in paclitaxel and docetaxel pharmacokinetic profiles. In this review, we provide preclinical and clinical data on several novel taxanes formulations and analogs which are currently US Food and Drug Administration (FDA)-approved or in clinical development in various solid tumor malignancies. Of the new taxanes nab-paclitaxel and cabazitaxel have enjoyed clinical success and are FDA-approved; while many of the other compounds described in this review are unlikely to be further developed for clinical use in daily practice. Furthermore, the successful clinical emergence of novel nontaxane microtubule-targeting chemotherapy agents such as epothilones and eribulin is liable to further restrict the development of novel taxanes.
Tight junction (TJ) proteins are involved in a number of cellular functions, including paracellular barrier formation, cell polarization, differentiation, and proliferation. Altered expression of TJ proteins was reported in various epithelial tumors. Here, we used tissue samples of human cutaneous squamous cell carcinoma (SCC), its precursor tumors, as well as sun-exposed and non-sun-exposed skin as a model system to investigate TJ protein alteration at various stages of tumorigenesis. We identified that a broader localization of zonula occludens protein (ZO)-1 and claudin-4 (Cldn-4) as well as downregulation of Cldn-1 in deeper epidermal layers is a frequent event in all the tumor entities as well as in sun-exposed skin, suggesting that these changes result from chronic UV irradiation. In contrast, SCC could be distinguished from the precursor tumors and sun-exposed skin by a frequent complete loss of occludin (Ocln). To elucidate the impact of down-regulation of Ocln, we performed Ocln siRNA experiments in human keratinocytes and uncovered that Ocln downregulation results in decreased epithelial cell-cell adhesion and reduced susceptibility to apoptosis induction by UVB or TNF-related apoptosis-inducing ligand (TRAIL), cellular characteristics for tumorigenesis. Furthermore, an influence on epidermal differentiation was observed, while there was no change of E-cadherin and vimentin, markers for epithelial-mesenchymal transition. Ocln knock-down altered Ca(2+)-homeostasis which may contribute to alterations of cell-cell adhesion and differentiation. As downregulation of Ocln is also seen in SCC derived from other tissues, as well as in other carcinomas, we suggest this as a common principle in tumor pathogenesis, which may be used as a target for therapeutic intervention.
The most compelling reason and primary goal of treating actinic keratoses is to prevent malignant transformation into invasive squamous cell carcinoma, and although there are well established guidelines outlining treatment modalities and regimens for squamous cell carcinoma, the more commonly encountered precancerous actinic lesions have no such standard. Many options are available with variable success and patient compliance rates. Prevention of these lesions is key, with sun protection being a must in treating aging patients with sun damage as it is never too late to begin protecting the skin.
Transformation is a complex process, involving many changes in the cell. In this work, we investigated the transcriptional changes that arose during the development of squamous cell carcinoma (SCC) in mice. Using microarray analysis, we looked at gene expression during different stages in cancer progression in 31 mice. By analyzing tumor progression in each mouse separately, we were able to define the global changes that were common to all 31 mice, as well as significant changes that occurred in fewer individuals. We found that different genes can contribute to the tumorigenic process in different mice, and that there are many ways to acquire the malignant properties defined by Hanahan and Weinberg as “hallmarks of cancer”. Eventually, however, all these changes lead to a very similar cancerous phenotype. The finding that gene expression is strongly heterogeneous in tumors that were induced by a standardized protocol in closely related mice underscores the need for molecular characterization of human tumors and personalized therapy.
We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due to its fully quantitative nature and high accuracy in each step of (i) detection, (ii) segmentation, and (iii) feature extraction. To evaluate our proposed computational framework, thirty patients received 2 (18)F-FDG-PET scans (60 scans total), at two different time points. Metastatic papillary renal cell carcinoma, cerebellar hemongioblastoma, non-small cell lung cancer, neurofibroma, lymphomatoid granulomatosis, lung neoplasm, neuroendocrine tumor, soft tissue thoracic mass, nonnecrotizing granulomatous inflammation, renal cell carcinoma with papillary and cystic features, diffuse large B-cell lymphoma, metastatic alveolar soft part sarcoma, and small cell lung cancer were included in this analysis. The radiotracer accumulation in patients' scans was automatically detected and segmented by the proposed segmentation algorithm. Delineated regions were used to extract shape and textural features, with the proposed adaptive feature extraction framework, as well as standardized uptake values (SUV) of uptake regions, to conduct a broad quantitative analysis. Evaluation of segmentation results indicates that our proposed segmentation algorithm has a mean dice similarity coefficient of 85.75±1.75%. We found that 28 of 68 extracted imaging features were correlated well with SUV(max) (p<0.05), and some of the textural features (such as entropy and maximum probability) were superior in predicting morphological changes of radiotracer uptake regions longitudinally, compared to single intensity feature such as SUV(max). We also found that integrating textural features with SUV measurements significantly improves the prediction accuracy of morphological changes (Spearman correlation coefficient = 0.8715, p<2e-16).
Epidermal squamous cell carcinoma is among the most common cancers in humans. These tumors are comprised of phenotypically diverse populations of cells that display varying potential for proliferation and differentiation. An important goal is identifying cells from this population that drive tumor formation. To enrich for tumor-forming cells, cancer cells were grown as spheroids in non-attached conditions. We show that spheroid-selected cells form faster growing and larger tumors in immune-compromised mice as compared to non-selected cells. Moreover, spheroid-selected cells gave rise to tumors following injection of as few as one hundred cells, suggesting these cells have enhanced tumor-forming potential. Cells isolated from spheroid-selected tumors retain an enhanced ability to grow as spheroids when grown in non-attached culture conditions. Thus, these tumor-forming cells retain their phenotype following in vivo passage as tumors. Detailed analysis reveals that spheroid-selected cultures are highly enriched for expression of epidermal stem cell and embryonic stem cell markers, including aldehyde dehydrogenase 1, keratin 15, CD200, keratin 19, Oct4, Bmi-1, Ezh2 and trimethylated histone H3. These studies indicate that a subpopulation of cells that possess stem cell-like properties and express stem cell markers can be derived from human epidermal cancer cells and that these cells display enhanced ability to drive tumor formation.
Nevoid basal cell carcinoma syndrome (Gorlin syndrome) is a rare autosomal dominant disorder characterized by numerous basal cell carcinomas, keratocystic odontogenic tumors of the jaws, and diverse developmental defects. This disorder is associated with mutations in tumor suppressor gene Patched 1 (PTCH1). We present two patients with Gorlin syndrome, one sporadic and one familial. Clinical examination, radiological and CT imaging, and mutation screening of PTCH1 gene were performed. Family members, as well as eleven healthy controls were included in the study. Both patients fulfilled the specific criteria for diagnosis of Gorlin syndrome. Molecular analysis of the first patient showed a novel frameshift mutation in exon 6 of PTCH1gene (c.903delT). Additionally, a somatic frameshift mutation in exon 21 (c.3524delT) along with germline mutation in exon 6 was detected in tumor-derived tissue sample of this patient. Analysis of the second patient, as well as two affected family members, revealed a novel nonsense germline mutation in exon 8 (c.1148 C>A).
B7-H4, one of the costimulatory molecules of B7 family, has been found to be widely expressed in many kinds of tumor tissues and to play an important part in tumor progression and poor prognosis. However, the role of B7-H4 in esophageal squamous cell carcinoma (ESCC) cells has not been elucidated. In this study, we found that, compared with normal esophageal tissue, B7-H4 was highly expressed in three ESCC cell lines, Eca109, TE1 and TE13. Besides, B7-H4 silence suppressed cells proliferation and colony formation. Additionally, compared with control cells, B7-H4 silence cells showed higher apoptosis rate, Bcl-2 and Survivin upregulation as well as BAX downregulation. Further study demonstrated that B7-H4 silence cells also exhibited reduction of IL-6 secretion, STAT3 activation and p-STAT3 translocation from cytoplasm to nucleus. Moreover, B7-H4 depletion inhibited the IL-6 secretion of control cells but not JAK2/STAT3 inhibitor FLLL32 treated cells. IL-6 receptor antagonist Tocilizumab didn’t block the p-JAK2 and p-STAT3 downregulation induced by B7-H4 silence. It was suggested that B7-H4 silence suppressed IL-6 secretion through JAK2/STAT3 inactivation. Furthermore, cells proliferation and colony formation were downregulated by Tocilizumab in control cells but not B7-H4 silence cells demonstrating that IL-6 upregulation induced by B7-H4 was necessary for cells growth. On the other hand, B7-H4 expression was downregulated by Tocilizumab. In all, our study provided the first evidence that B7-H4 facilitated ESCC cells proliferation through promoting IL-6/STAT3 positive loopback pathway activation. This article is protected by copyright. All rights reserved.
Skin cancer, the most common human malignancy, is primarily diagnosed visually, beginning with an initial clinical screening and followed potentially by dermoscopic analysis, a biopsy and histopathological examination. Automated classification of skin lesions using images is a challenging task owing to the fine-grained variability in the appearance of skin lesions. Deep convolutional neural networks (CNNs) show potential for general and highly variable tasks across many fine-grained object categories. Here we demonstrate classification of skin lesions using a single CNN, trained end-to-end from images directly, using only pixels and disease labels as inputs. We train a CNN using a dataset of 129,450 clinical images-two orders of magnitude larger than previous datasets-consisting of 2,032 different diseases. We test its performance against 21 board-certified dermatologists on biopsy-proven clinical images with two critical binary classification use cases: keratinocyte carcinomas versus benign seborrheic keratoses; and malignant melanomas versus benign nevi. The first case represents the identification of the most common cancers, the second represents the identification of the deadliest skin cancer. The CNN achieves performance on par with all tested experts across both tasks, demonstrating an artificial intelligence capable of classifying skin cancer with a level of competence comparable to dermatologists. Outfitted with deep neural networks, mobile devices can potentially extend the reach of dermatologists outside of the clinic. It is projected that 6.3 billion smartphone subscriptions will exist by the year 2021 (ref. 13) and can therefore potentially provide low-cost universal access to vital diagnostic care.